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ORCIDAram Galstyan
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- affiliation: University of Southern California, Los Angeles, USA
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2020 – today
- 2024
[c129]Tianyi Yan, Fei Wang, James Y. Huang, Wenxuan Zhou, Fan Yin, Aram Galstyan, Wenpeng Yin, Muhao Chen:
Contrastive Instruction Tuning. ACL (Findings) 2024: 10288-10302- [c128]Elan Markowitz, Anil Ramakrishna, Jwala Dhamala, Ninareh Mehrabi, Charith Peris, Rahul Gupta, Kai-Wei Chang, Aram Galstyan:
Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs. ACL (1) 2024: 12302-12319 - [c127]Myrl G. Marmarelis, Fred Morstatter, Aram Galstyan, Greg Ver Steeg:
Policy Learning for Localized Interventions from Observational Data. AISTATS 2024: 4456-4464 - [c126]Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan, Fred Morstatter:
Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding. CLeaR 2024: 18-40 - [c125]Yi Ren Fung, Anoop Kumar, Aram Galstyan, Heng Ji, Prem Natarajan:
Agenda-Driven Question Generation: A Case Study in the Courtroom Domain. LREC/COLING 2024: 572-583 - [c124]Kshitij Mishra, Tamer Soliman, Anil Ramakrishna, Aram Galstyan, Anoop Kumar:
Correcting Language Model Outputs by Editing Salient Layers. EACL (Findings) 2024: 1295-1305 - [c123]Yao Qiang, Subhrangshu Nandi, Ninareh Mehrabi, Greg Ver Steeg, Anoop Kumar, Anna Rumshisky, Aram Galstyan:
Prompt Perturbation Consistency Learning for Robust Language Models. EACL (Findings) 2024: 1357-1370 - [c122]Jinghan Jia, Abi Komma, Timothy Leffel, Xujun Peng, Ajay Nagesh, Tamer Soliman, Aram Galstyan, Anoop Kumar:
Leveraging LLMs for Dialogue Quality Measurement. NAACL (Industry Track) 2024: 359-367 - [c121]Roy Siegelmann, Ninareh Mehrabi, Palash Goyal, Prasoon Goyal, Lisa Bauer, Jwala Dhamala, Aram Galstyan, Rahul Gupta, Reza Ghanadan:
MICo: Preventative Detoxification of Large Language Models through Inhibition Control. NAACL-HLT (Findings) 2024: 1696-1703 - [c120]Anaelia Ovalle, Ninareh Mehrabi, Palash Goyal, Jwala Dhamala, Kai-Wei Chang, Richard S. Zemel, Aram Galstyan, Yuval Pinter, Rahul Gupta:
Tokenization Matters: Navigating Data-Scarce Tokenization for Gender Inclusive Language Technologies. NAACL-HLT (Findings) 2024: 1739-1756 - [c119]Junyi Li, Charith Peris, Ninareh Mehrabi, Palash Goyal, Kai-Wei Chang, Aram Galstyan, Richard S. Zemel, Rahul Gupta:
The steerability of large language models toward data-driven personas. NAACL-HLT 2024: 7290-7305 - [i124]Tianyi Yan, Fei Wang, James Y. Huang, Wenxuan Zhou, Fan Yin, Aram Galstyan, Wenpeng Yin, Muhao Chen:
Contrastive Instruction Tuning. CoRR abs/2402.11138 (2024) - [i123]Yao Qiang, Subhrangshu Nandi, Ninareh Mehrabi, Greg Ver Steeg, Anoop Kumar, Anna Rumshisky, Aram Galstyan:
Prompt Perturbation Consistency Learning for Robust Language Models. CoRR abs/2402.15833 (2024) - [i122]Jinghan Jia, Abi Komma, Timothy Leffel, Xujun Peng, Ajay Nagesh, Tamer Soliman, Aram Galstyan, Anoop Kumar:
Leveraging LLMs for Dialogue Quality Measurement. CoRR abs/2406.17304 (2024) - [i121]Elan Markowitz, Anil Ramakrishna, Jwala Dhamala, Ninareh Mehrabi, Charith Peris, Rahul Gupta, Kai-Wei Chang, Aram Galstyan:
Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs. CoRR abs/2407.21358 (2024) - 2023
- [j21]Daniel M. Benjamin, Fred Morstatter, Ali E. Abbas, Andrés Abeliuk, Pavel Atanasov, Stephen Bennett, Andreas Beger
, Saurabh Birari, David V. Budescu, Michele Catasta, Emilio Ferrara, Lucas Haravitch, Mark Himmelstein, K. S. M. Tozammel Hossain, Yuzhong Huang, Woojeong Jin, Regina Joseph, Jure Leskovec, Akira Matsui, Mehrnoosh Mirtaheri, Xiang Ren, Gleb Satyukov, Rajiv Sethi, Amandeep Singh, Rok Sosic, Mark Steyvers, Pedro A. Szekely, Michael D. Ward, Aram Galstyan:
Hybrid forecasting of geopolitical events†. AI Mag. 44(1): 112-128 (2023) - [c118]Mohammad Rostami, Aram Galstyan:
Overcoming Concept Shift in Domain-Aware Settings through Consolidated Internal Distributions. AAAI 2023: 9623-9631 - [c117]Abishek Komma, Nagesh Panyam Chandrasekarasastry, Timothy Leffel, Anuj Goyal, Angeliki Metallinou, Spyros Matsoukas, Aram Galstyan:
Toward More Accurate and Generalizable Evaluation Metrics for Task-Oriented Dialogs. ACL (industry) 2023: 186-195 - [c116]Arghya Datta, Subhrangshu Nandi, Jingcheng Xu, Greg Ver Steeg, He Xie, Anoop Kumar, Aram Galstyan:
Measuring and Mitigating Local Instability in Deep Neural Networks. ACL (Findings) 2023: 2810-2823 - [c115]Sarik Ghazarian, Yijia Shao, Rujun Han, Aram Galstyan, Nanyun Peng:
ACCENT: An Automatic Event Commonsense Evaluation Metric for Open-Domain Dialogue Systems. ACL (1) 2023: 4398-4419 - [c114]Mehrnoosh Mirtaheri, Mohammad Rostami, Aram Galstyan:
History repeats: Overcoming catastrophic forgetting for event-centric temporal knowledge graph completion. ACL (Findings) 2023: 7740-7755 - [c113]Kuan-Hao Huang, Varun Iyer, I-Hung Hsu, Anoop Kumar, Kai-Wei Chang, Aram Galstyan:
ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation. ACL (1) 2023: 8047-8061 - [c112]Neal Lawton, Anoop Kumar, Govind Thattai, Aram Galstyan, Greg Ver Steeg:
Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models. ACL (Findings) 2023: 8506-8515 - [c111]Umang Gupta, Aram Galstyan, Greg Ver Steeg:
Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning. ACL (Findings) 2023: 12612-12629 - [c110]Ninareh Mehrabi, Palash Goyal, Apurv Verma, Jwala Dhamala, Varun Kumar, Qian Hu, Kai-Wei Chang, Richard S. Zemel, Aram Galstyan, Rahul Gupta:
Resolving Ambiguities in Text-to-Image Generative Models. ACL (1) 2023: 14367-14388 - [c109]Zheng Chen, Ziyan Jiang, Fan Yang, Zhankui He, Yupeng Hou, Eunah Cho, Julian J. McAuley, Aram Galstyan, Xiaohua Hu, Jie Yang:
The First Workshop on Personalized Generative AI @ CIKM 2023: Personalization Meets Large Language Models. CIKM 2023: 5267-5270 - [c108]Elan Sopher Markowitz, Aram Galstyan:
StATIK+: Structure and Text for Inductive Knowledge Graph Modeling and Paths towards Enterprise Implementations. EKG-LLM@CIKM 2023 - [c107]Zheng Chen, Ziyan Jiang, Fan Yang, Eunah Cho, Xing Fan, Xiaojiang Huang, Yanbin Lu, Aram Galstyan:
Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding. EMNLP (Industry Track) 2023: 811-819 - [c106]Mohammad Rostami, Digbalay Bose, Shrikanth Narayanan, Aram Galstyan:
Domain Adaptation for Sentiment Analysis Using Robust Internal Representations. EMNLP (Findings) 2023: 11484-11498 - [c105]Anaelia Ovalle, Palash Goyal, Jwala Dhamala, Zachary Jaggers, Kai-Wei Chang, Aram Galstyan, Richard S. Zemel, Rahul Gupta:
"I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation. FAccT 2023: 1246-1266 - [c104]Mohammad Rostami, Aram Galstyan:
Cognitively Inspired Learning of Incremental Drifting Concepts. IJCAI 2023: 3058-3066 - [c103]Elizabeth Haddad, Myrl G. Marmarelis, Talia M. Nir, Aram Galstyan, Greg Ver Steeg, Neda Jahanshad:
Causal Sensitivity Analysis for Hidden Confounding: Modeling the Sex-Specific Role of Diet on the Aging Brain. MLCN@MICCAI 2023: 91-101 - [c102]Myrl G. Marmarelis, Elizabeth Haddad, Andrew Jesson, Neda Jahanshad, Aram Galstyan, Greg Ver Steeg:
Partial identification of dose responses with hidden confounders. UAI 2023: 1368-1379 - [c101]Rahul Gupta, Lisa Bauer, Kai-Wei Chang, Jwala Dhamala, Aram Galstyan, Palash Goyal, Qian Hu, Avni Khatri, Rohit Parimi, Charith Peris, Apurv Verma, Richard S. Zemel, Prem Natarajan:
Incorporating Fairness in Large Scale NLU Systems. WSDM 2023: 1289-1290 - [i120]Sarik Ghazarian, Yijia Shao, Rujun Han, Aram Galstyan, Nanyun Peng:
ACCENT: An Automatic Event Commonsense Evaluation Metric for Open-Domain Dialogue Systems. CoRR abs/2305.07797 (2023) - [i119]Anaelia Ovalle, Palash Goyal, Jwala Dhamala, Zachary Jaggers, Kai-Wei Chang, Aram Galstyan, Richard S. Zemel, Rahul Gupta:
"I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation. CoRR abs/2305.09941 (2023) - [i118]Arghya Datta, Subhrangshu Nandi, Jingcheng Xu, Greg Ver Steeg, He Xie, Anoop Kumar, Aram Galstyan:
Measuring and Mitigating Local Instability in Deep Neural Networks. CoRR abs/2305.10625 (2023) - [i117]Kuan-Hao Huang, Varun Iyer, I-Hung Hsu, Anoop Kumar, Kai-Wei Chang, Aram Galstyan:
ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation. CoRR abs/2305.16585 (2023) - [i116]Neal Lawton, Anoop Kumar, Govind Thattai, Aram Galstyan, Greg Ver Steeg:
Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models. CoRR abs/2305.16597 (2023) - [i115]Mehrnoosh Mirtaheri, Mohammad Rostami, Aram Galstyan:
History Repeats: Overcoming Catastrophic Forgetting For Event-Centric Temporal Knowledge Graph Completion. CoRR abs/2305.18675 (2023) - [i114]Umang Gupta, Aram Galstyan, Greg Ver Steeg:
Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning. CoRR abs/2305.19264 (2023) - [i113]Abishek Komma, Nagesh Panyam Chandrasekarasastry, Timothy Leffel, Anuj Goyal, Angeliki Metallinou, Spyros Matsoukas, Aram Galstyan:
Toward More Accurate and Generalizable Evaluation Metrics for Task-Oriented Dialogs. CoRR abs/2306.03984 (2023) - [i112]Elan Markowitz, Ziyan Jiang, Fan Yang, Xing Fan, Tony Chen, Greg Ver Steeg, Aram Galstyan:
Multi-Task Knowledge Enhancement for Zero-Shot and Multi-Domain Recommendation in an AI Assistant Application. CoRR abs/2306.06302 (2023) - [i111]Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan, Fred Morstatter:
Tighter Prediction Intervals for Causal Outcomes Under Hidden Confounding. CoRR abs/2306.09520 (2023) - [i110]Ninareh Mehrabi, Palash Goyal, Christophe Dupuy, Qian Hu, Shalini Ghosh, Richard S. Zemel, Kai-Wei Chang, Aram Galstyan, Rahul Gupta:
FLIRT: Feedback Loop In-context Red Teaming. CoRR abs/2308.04265 (2023) - [i109]Junyi Li, Ninareh Mehrabi, Charith Peris, Palash Goyal, Kai-Wei Chang, Aram Galstyan, Richard S. Zemel, Rahul Gupta:
On the steerability of large language models toward data-driven personas. CoRR abs/2311.04978 (2023) - [i108]Ninareh Mehrabi, Palash Goyal, Anil Ramakrishna, Jwala Dhamala, Shalini Ghosh, Richard S. Zemel, Kai-Wei Chang, Aram Galstyan, Rahul Gupta:
JAB: Joint Adversarial Prompting and Belief Augmentation. CoRR abs/2311.09473 (2023) - [i107]Anaelia Ovalle, Ninareh Mehrabi, Palash Goyal, Jwala Dhamala, Kai-Wei Chang, Richard S. Zemel, Aram Galstyan, Rahul Gupta:
Are you talking to ['xem'] or ['x', 'em']? On Tokenization and Addressing Misgendering in LLMs with Pronoun Tokenization Parity. CoRR abs/2312.11779 (2023) - 2022
- [j20]Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, Aram Galstyan:
A Survey on Bias and Fairness in Machine Learning. ACM Comput. Surv. 54(6): 115:1-115:35 (2022) - [j19]K. S. M. Tozammel Hossain, Hrayr Harutyunyan, Yue Ning, Brendan Kennedy, Naren Ramakrishnan, Aram Galstyan:
Identifying geopolitical event precursors using attention-based LSTMs. Frontiers Artif. Intell. 5 (2022) - [j18]Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan:
A Metric Space for Point Process Excitations. J. Artif. Intell. Res. 73 (2022) - [c100]Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta, Varun Kumar, Jwala Dhamala, Aram Galstyan:
On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations. ACL (2) 2022: 561-570 - [c99]Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan:
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. ACL (Findings) 2022: 658-678 - [c98]Sarik Ghazarian, Nuan Wen, Aram Galstyan, Nanyun Peng:
DEAM: Dialogue Coherence Evaluation using AMR-based Semantic Manipulations. ACL (1) 2022: 771-785 - [c97]Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan:
Failure Modes of Domain Generalization Algorithms. CVPR 2022: 19055-19064 - [c96]Kuan-Hao Huang, Varun Iyer, Anoop Kumar, Sriram Venkatapathy, Kai-Wei Chang, Aram Galstyan:
Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations. EMNLP (Findings) 2022: 1547-1554 - [c95]Anoop Kumar, Pankaj Kumar Sharma, Aravind Illa, Sriram Venkatapathy, Subhrangshu Nandi, Pritam Varma, Anurag Dwarakanath, Aram Galstyan:
Learning Under Label Noise for Robust Spoken Language Understanding systems. INTERSPEECH 2022: 3463-3467 - [c94]Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan:
Formal limitations of sample-wise information-theoretic generalization bounds. ITW 2022: 440-445 - [c93]Judith Gaspers, Anoop Kumar, Greg Ver Steeg, Aram Galstyan:
Temporal Generalization for Spoken Language Understanding. NAACL-HLT (Industry Papers) 2022: 37-44 - [c92]Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Murali Annavaram, Aram Galstyan, Greg Ver Steeg:
StATIK: Structure and Text for Inductive Knowledge Graph Completion. NAACL-HLT (Findings) 2022: 604-615 - [c91]Ninareh Mehrabi, Ahmad Beirami, Fred Morstatter, Aram Galstyan:
Robust Conversational Agents against Imperceptible Toxicity Triggers. NAACL-HLT 2022: 2831-2847 - [c90]Jwala Dhamala, Varun Kumar, Rahul Gupta, Kai-Wei Chang, Aram Galstyan:
An Analysis of The Effects of Decoding Algorithms on Fairness in Open-Ended Language Generation. SLT 2022: 655-662 - [i106]Sarik Ghazarian, Nuan Wen, Aram Galstyan, Nanyun Peng:
DEAM: Dialogue Coherence Evaluation using AMR-based Semantic Manipulations. CoRR abs/2203.09711 (2022) - [i105]Marcin Abram, Keith Burghardt, Greg Ver Steeg, Aram Galstyan, Rémi Dingreville:
Inferring topological transitions in pattern-forming processes with self-supervised learning. CoRR abs/2203.10204 (2022) - [i104]Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan:
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. CoRR abs/2203.12574 (2022) - [i103]Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta, Varun Kumar, Jwala Dhamala, Aram Galstyan:
On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations. CoRR abs/2203.13928 (2022) - [i102]Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan:
Bounding the Effects of Continuous Treatments for Hidden Confounders. CoRR abs/2204.11206 (2022) - [i101]Ninareh Mehrabi, Ahmad Beirami, Fred Morstatter, Aram Galstyan:
Robust Conversational Agents against Imperceptible Toxicity Triggers. CoRR abs/2205.02392 (2022) - [i100]Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan:
Formal limitations of sample-wise information-theoretic generalization bounds. CoRR abs/2205.06915 (2022) - [i99]Jwala Dhamala, Varun Kumar, Rahul Gupta, Kai-Wei Chang, Aram Galstyan:
An Analysis of the Effects of Decoding Algorithms on Fairness in Open-Ended Language Generation. CoRR abs/2210.03826 (2022) - [i98]Kuan-Hao Huang, Varun Iyer, Anoop Kumar, Sriram Venkatapathy, Kai-Wei Chang, Aram Galstyan:
Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations. CoRR abs/2211.00881 (2022) - [i97]Ninareh Mehrabi, Palash Goyal, Apurv Verma, Jwala Dhamala, Varun Kumar, Qian Hu, Kai-Wei Chang, Richard S. Zemel, Aram Galstyan, Rahul Gupta:
Is the Elephant Flying? Resolving Ambiguities in Text-to-Image Generative Models. CoRR abs/2211.12503 (2022) - 2021
- [j17]Shushan Arakelyan, Sima Arasteh, Christophe Hauser, Erik Kline, Aram Galstyan:
Bin2vec: learning representations of binary executable programs for security tasks. Cybersecur. 4(1) (2021) - [j16]Kyle Reing, Greg Ver Steeg, Aram Galstyan:
Discovering Higher-Order Interactions Through Neural Information Decomposition. Entropy 23(1): 79 (2021) - [j15]Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Fred Morstatter, Greg Ver Steeg, Aram Galstyan:
Identifying and Analyzing Cryptocurrency Manipulations in Social Media. IEEE Trans. Comput. Soc. Syst. 8(3): 607-617 (2021) - [c89]Ninareh Mehrabi, Muhammad Naveed, Fred Morstatter, Aram Galstyan:
Exacerbating Algorithmic Bias through Fairness Attacks. AAAI 2021: 8930-8938 - [c88]Woojeong Jin, Rahul Khanna, Suji Kim, Dong-Ho Lee, Fred Morstatter, Aram Galstyan, Xiang Ren:
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data. ACL/IJCNLP (1) 2021: 4636-4650 - [c87]James O'Neill, Greg Ver Steeg, Aram Galstyan:
Layer-Wise Neural Network Compression via Layer Fusion. ACML 2021: 1381-1396 - [c86]Kyle Reing, Greg Ver Steeg, Aram Galstyan:
Influence Decompositions For Neural Network Attribution. AISTATS 2021: 2710-2718 - [c85]Mehrnoosh Mirtaheri, Mohammad Rostami, Xiang Ren, Fred Morstatter, Aram Galstyan:
One-shot Learning for Temporal Knowledge Graphs. AKBC 2021 - [c84]Ninareh Mehrabi, Pei Zhou, Fred Morstatter, Jay Pujara, Xiang Ren, Aram Galstyan:
Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources. EMNLP (1) 2021: 5016-5033 - [c83]Jiawei Ma, Hanchen Xie, Guangxing Han, Shih-Fu Chang, Aram Galstyan, Wael Abd-Almageed:
Partner-Assisted Learning for Few-Shot Image Classification. ICCV 2021: 10553-10562 - [c82]Elan Sopher Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan:
Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. ICLR 2021 - [c81]Sarik Ghazarian, Zixi Liu, Tuhin Chakrabarty, Xuezhe Ma, Aram Galstyan, Nanyun Peng:
DiSCoL: Toward Engaging Dialogue Systems through Conversational Line Guided Response Generation. NAACL-HLT (Demonstrations) 2021: 26-34 - [c80]Sarik Ghazarian, Zixi Liu, Akash SM, Ralph M. Weischedel, Aram Galstyan, Nanyun Peng:
Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation. NAACL-HLT 2021: 4334-4344 - [c79]Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan:
Implicit SVD for Graph Representation Learning. NeurIPS 2021: 8419-8431 - [c78]Greg Ver Steeg, Aram Galstyan:
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling. NeurIPS 2021: 11012-11025 - [c77]Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan:
Information-theoretic generalization bounds for black-box learning algorithms. NeurIPS 2021: 24670-24682 - [c76]Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood:
q-Paths: Generalizing the geometric annealing path using power means. UAI 2021: 1938-1947 - [c75]Hanchen Xie, Mohamed E. Hussein, Aram Galstyan, Wael Abd-Almageed:
MUSCLE: Strengthening Semi-Supervised Learning Via Concurrent Unsupervised Learning Using Mutual Information Maximization. WACV 2021: 2585-2594 - [i96]Sarik Ghazarian, Zixi Liu, Tuhin Chakrabarty, Xuezhe Ma, Aram Galstyan, Nanyun Peng:
DiSCoL: Toward Engaging Dialogue Systems through Conversational Line Guided Response Generation. CoRR abs/2102.02191 (2021) - [i95]Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan:
Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. CoRR abs/2102.04350 (2021) - [i94]Sami Abu-El-Haija, Valentino Crespi, Greg Ver Steeg, Aram Galstyan:
Fast Graph Learning with Unique Optimal Solutions. CoRR abs/2102.08530 (2021) - [i93]Ninareh Mehrabi, Pei Zhou, Fred Morstatter, Jay Pujara, Xiang Ren, Aram Galstyan:
Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources. CoRR abs/2103.11320 (2021) - [i92]Sarik Ghazarian, Zixi Liu, Akash SM, Ralph M. Weischedel, Aram Galstyan, Nanyun Peng:
Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation. CoRR abs/2104.05801 (2021) - [i91]Valentino Crespi, Wes Hardaker, Sami Abu-El-Haija, Aram Galstyan:
Identifying botnet IP address clusters using natural language processing techniques on honeypot command logs. CoRR abs/2104.10232 (2021) - [i90]Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood:
q-Paths: Generalizing the Geometric Annealing Path using Power Means. CoRR abs/2107.00745 (2021) - [i89]Mohammad Rostami, Aram Galstyan:
Domain Adaptation for Sentiment Analysis Using Increased Intraclass Separation. CoRR abs/2107.01598 (2021) - [i88]Ninareh Mehrabi, Umang Gupta, Fred Morstatter, Greg Ver Steeg, Aram Galstyan:
Attributing Fair Decisions with Attention Interventions. CoRR abs/2109.03952 (2021) - [i87]Jiawei Ma, Hanchen Xie, Guangxing Han, Shih-Fu Chang, Aram Galstyan, Wael Abd-Almageed:
Partner-Assisted Learning for Few-Shot Image Classification. CoRR abs/2109.07607 (2021) - [i86]Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan:
Information-theoretic generalization bounds for black-box learning algorithms. CoRR abs/2110.01584 (2021) - [i85]Mohammad Rostami, Aram Galstyan:
Cognitively Inspired Learning of Incremental Drifting Concepts. CoRR abs/2110.04662 (2021) - [i84]Greg Ver Steeg, Aram Galstyan:
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling. CoRR abs/2111.02434 (2021) - [i83]Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan:
Implicit SVD for Graph Representation Learning. CoRR abs/2111.06312 (2021) - [i82]Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan:
Failure Modes of Domain Generalization Algorithms. CoRR abs/2111.13733 (2021) - 2020
- [j14]Amir Ghasemian, Homa Hosseinmardi, Aram Galstyan, Edoardo M. Airoldi, Aaron Clauset:
Stacking models for nearly optimal link prediction in complex networks. Proc. Natl. Acad. Sci. USA 117(38): 23393-23400 (2020) - [j13]Kyle Reing, Greg Ver Steeg, Aram Galstyan:
Maximizing Multivariate Information With Error-Correcting Codes. IEEE Trans. Inf. Theory 66(5): 2683-2695 (2020) - [c74]Sahil Garg, Irina Rish, Guillermo A. Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan:
Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. AAAI 2020: 3970-3979 - [c73]Sarik Ghazarian, Ralph M. Weischedel, Aram Galstyan, Nanyun Peng:
Predictive Engagement: An Efficient Metric for Automatic Evaluation of Open-Domain Dialogue Systems. AAAI 2020: 7789-7796 - [c72]Yuzhong Huang, Andrés Abeliuk, Fred Morstatter, Pavel Atanasov, Aram Galstyan:
Anchor Attention for Hybrid Crowd Forecasts Aggregation. AAMAS 2020: 1869-1871 - [c71]Ninareh Mehrabi, Thamme Gowda, Fred Morstatter, Nanyun Peng, Aram Galstyan:
Man is to Person as Woman is to Location: Measuring Gender Bias in Named Entity Recognition. HT 2020: 231-232 - [c70]Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan:
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. ICML 2020: 1111-1122 - [c69]Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan:
Improving generalization by controlling label-noise information in neural network weights. ICML 2020: 4071-4081 - [c68]Di Huang, Zihao He, Yuzhong Huang, Kexuan Sun, Sami Abu-El-Haija, Bryan Perozzi, Kristina Lerman, Fred Morstatter, Aram Galstyan:
Graph Embedding with Personalized Context Distribution. WWW (Companion Volume) 2020: 655-661 - [i81]Shushan Arakelyan, Christophe Hauser, Erik Kline, Aram Galstyan:
Towards Learning Representations of Binary Executable Files for Security Tasks. CoRR abs/2002.03388 (2020) - [i80]Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan:
Improving Generalization by Controlling Label-Noise Information in Neural Network Weights. CoRR abs/2002.07933 (2020) - [i79]Yuzhong Huang, Andrés Abeliuk, Fred Morstatter, Pavel Atanasov, Aram Galstyan:
Anchor Attention for Hybrid Crowd Forecasts Aggregation. CoRR abs/2003.12447 (2020) - [i78]Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan:
Event Cartography: Latent Point Process Embeddings. CoRR abs/2005.02515 (2020) - [i77]Mohammad Rostami, Aram Galstyan:
Sequential Unsupervised Domain Adaptation through Prototypical Distributions. CoRR abs/2007.00197 (2020) - [i76]Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan:
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. CoRR abs/2007.00642 (2020) - [i75]Tigran Galstyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan:
Robust Classification under Class-Dependent Domain Shift. CoRR abs/2007.05335 (2020) - [i74]James O'Neill, Greg Ver Steeg, Aram Galstyan:
Compressing Deep Neural Networks via Layer Fusion. CoRR abs/2007.14917 (2020) - [i73]Akira Matsui, Emilio Ferrara, Fred Morstatter, Andrés Abeliuk, Aram Galstyan:
Leveraging Clickstream Trajectories to Reveal Low-Quality Workers in Crowdsourced Forecasting Platforms. CoRR abs/2009.01966 (2020) - [i72]Mehrnoosh Mirtaheri, Mohammad Rostami, Xiang Ren, Fred Morstatter, Aram Galstyan:
One-shot Learning for Temporal Knowledge Graphs. CoRR abs/2010.12144 (2020) - [i71]Hanchen Xie, Mohamed E. Hussein, Aram Galstyan, Wael Abd-Almageed:
MUSCLE: Strengthening Semi-Supervised Learning Via Concurrent Unsupervised Learning Using Mutual Information Maximization. CoRR abs/2012.00150 (2020) - [i70]Rob Brekelmans, Vaden Masrani, Thang Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen:
Annealed Importance Sampling with q-Paths. CoRR abs/2012.07823 (2020) - [i69]Ninareh Mehrabi, Muhammad Naveed, Fred Morstatter, Aram Galstyan:
Exacerbating Algorithmic Bias through Fairness Attacks. CoRR abs/2012.08723 (2020) - [i68]Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg:
Likelihood Ratio Exponential Families. CoRR abs/2012.15480 (2020)
2010 – 2019
- 2019
- [c67]Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo A. Cecchi, Shuyang Gao:
Kernelized Hashcode Representations for Relation Extraction. AAAI 2019: 6431-6440 - [c66]Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan:
Auto-Encoding Total Correlation Explanation. AISTATS 2019: 1157-1166 - [c65]Ninareh Mehrabi, Fred Morstatter, Nanyun Peng, Aram Galstyan:
Debiasing community detection: the importance of lowly connected nodes. ASONAM 2019: 509-512 - [c64]Hrant Khachatrian, Lilit Nersisyan, Karen Hambardzumyan, Tigran Galstyan, Anna Hakobyan, Arsen Arakelyan, Andrey Rzhetsky, Aram Galstyan:
BioRelEx 1.0: Biological Relation Extraction Benchmark. BioNLP@ACL 2019: 176-190 - [c63]Rujun Han, I-Hung Hsu, Mu Yang, Aram Galstyan, Ralph M. Weischedel, Nanyun Peng:
Deep Structured Neural Network for Event Temporal Relation Extraction. CoNLL 2019: 666-106 - [c62]Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo A. Cecchi:
Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction. EMNLP/IJCNLP (1) 2019: 4024-4034 - [c61]Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan:
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. ICML 2019: 21-29 - [c60]Fred Morstatter, Aram Galstyan, Gleb Satyukov, Daniel Benjamin, Andrés Abeliuk, Mehrnoosh Mirtaheri, K. S. M. Tozammel Hossain, Pedro A. Szekely, Emilio Ferrara, Akira Matsui, Mark Steyvers, Stephen Bennett, David V. Budescu, Mark Himmelstein, Michael D. Ward, Andreas Beger, Michele Catasta, Rok Sosic, Jure Leskovec, Pavel Atanasov, Regina Joseph, Rajiv Sethi, Ali E. Abbas:
SAGE: A Hybrid Geopolitical Event Forecasting System. IJCAI 2019: 6557-6559 - [c59]Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg:
Exact Rate-Distortion in Autoencoders via Echo Noise. NeurIPS 2019: 3884-3895 - [c58]Greg Ver Steeg, Hrayr Harutyunyan, Daniel Moyer, Aram Galstyan:
Fast structure learning with modular regularization. NeurIPS 2019: 15567-15577 - [c57]Yike Liu, Linhong Zhu, Pedro A. Szekely, Aram Galstyan, Danai Koutra:
Coupled Clustering of Time-Series and Networks. SDM 2019: 531-539 - [i67]Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Fred Morstatter, Greg Ver Steeg, Aram Galstyan:
Identifying and Analyzing Cryptocurrency Manipulations in Social Media. CoRR abs/1902.03110 (2019) - [i66]Ninareh Mehrabi, Fred Morstatter, Nanyun Peng, Aram Galstyan:
Debiasing Community Detection: The Importance of Lowly-Connected Nodes. CoRR abs/1903.08136 (2019) - [i65]Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg:
Exact Rate-Distortion in Autoencoders via Echo Noise. CoRR abs/1904.07199 (2019) - [i64]Sarik Ghazarian, Johnny Tian-Zheng Wei, Aram Galstyan, Nanyun Peng:
Better Automatic Evaluation of Open-Domain Dialogue Systems with Contextualized Embeddings. CoRR abs/1904.10635 (2019) - [i63]Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Hrayr Harutyunyan, Nazanin Alipourfard, Kristina Lerman, Greg Ver Steeg, Aram Galstyan:
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. CoRR abs/1905.00067 (2019) - [i62]Hrayr Harutyunyan, Daniel Moyer, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan:
Efficient Covariance Estimation from Temporal Data. CoRR abs/1905.13276 (2019) - [i61]Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, Aram Galstyan:
A Survey on Bias and Fairness in Machine Learning. CoRR abs/1908.09635 (2019) - [i60]Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo A. Cecchi:
Nearly-Unsupervised Hashcode Representations for Relation Extraction. CoRR abs/1909.03881 (2019) - [i59]Amir Ghasemian, Homa Hosseinmardi, Aram Galstyan, Edoardo M. Airoldi, Aaron Clauset:
Stacking Models for Nearly Optimal Link Prediction in Complex Networks. CoRR abs/1909.07578 (2019) - [i58]Rujun Han, I-Hung Hsu, Mu Yang, Aram Galstyan, Ralph M. Weischedel, Nanyun Peng:
Deep Structured Neural Network for Event Temporal Relation Extraction. CoRR abs/1909.10094 (2019) - [i57]Ninareh Mehrabi, Thamme Gowda, Fred Morstatter, Nanyun Peng, Aram Galstyan:
Man is to Person as Woman is to Location: Measuring Gender Bias in Named Entity Recognition. CoRR abs/1910.10872 (2019) - [i56]Sarik Ghazarian, Ralph M. Weischedel, Aram Galstyan, Nanyun Peng:
Predictive Engagement: An Efficient Metric For Automatic Evaluation of Open-Domain Dialogue Systems. CoRR abs/1911.01456 (2019) - 2018
- [j12]Armen E. Allahverdyan, Aram Galstyan, Ali E. Abbas, Zbigniew R. Struzik:
Adaptive decision making via entropy minimization. Int. J. Approx. Reason. 103: 270-287 (2018) - [j11]Palash Goyal, Homa Hosseinmardi, Emilio Ferrara, Aram Galstyan:
Capturing Edge Attributes via Network Embedding. IEEE Trans. Comput. Soc. Syst. 5(4): 907-917 (2018) - [c56]Shushan Arakelyan, Fred Morstatter, Margaret Martin, Emilio Ferrara, Aram Galstyan:
Mining and Forecasting Career Trajectories of Music Artists. HT 2018: 11-19 - [c55]Palash Goyal, Homa Hosseinmardi, Emilio Ferrara, Aram Galstyan:
Embedding Networks with Edge Attributes. HT 2018: 38-42 - [c54]Sahil Garg, Guillermo A. Cecchi, Irina Rish, Shuyang Gao, Greg Ver Steeg, Sarik Ghazarian, Palash Goyal, Aram Galstyan:
Dialogue Modeling Via Hash Functions. LaCATODA@IJCAI 2018: 24-36 - [c53]Daniel Moyer, Shuyang Gao, Rob Brekelmans, Aram Galstyan, Greg Ver Steeg:
Invariant Representations without Adversarial Training. NeurIPS 2018: 9102-9111 - [c52]Neal Lawton, Greg Ver Steeg, Aram Galstyan:
A Forest Mixture Bound for Block-Free Parallel Inference. UAI 2018: 968-977 - [c51]Fred Morstatter, Yunqiu Shao, Aram Galstyan, Shanika Karunasekera:
From Alt-Right to Alt-Rechts: Twitter Analysis of the 2017 German Federal Election. WWW (Companion Volume) 2018: 621-628 - [i55]Sahil Garg, Greg Ver Steeg, Aram Galstyan:
Stochastic Learning of Nonstationary Kernels for Natural Language Modeling. CoRR abs/1801.03911 (2018) - [i54]Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan:
Auto-Encoding Total Correlation Explanation. CoRR abs/1802.05822 (2018) - [i53]Armen E. Allahverdyan, Aram Galstyan, Ali E. Abbas, Zbigniew R. Struzik:
Adaptive prior probabilities via optimization of risk and entropy. CoRR abs/1803.06638 (2018) - [i52]Palash Goyal, Homa Hosseinmardi, Emilio Ferrara, Aram Galstyan:
Capturing Edge Attributes via Network Embedding. CoRR abs/1805.03280 (2018) - [i51]Shushan Arakelyan, Fred Morstatter, Margaret Martin, Emilio Ferrara, Aram Galstyan:
Mining and Forecasting Career Trajectories of Music Artists. CoRR abs/1805.03324 (2018) - [i50]Neal Lawton, Aram Galstyan, Greg Ver Steeg:
A Forest Mixture Bound for Block-Free Parallel Inference. CoRR abs/1805.06951 (2018) - [i49]Daniel Moyer, Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan:
Evading the Adversary in Invariant Representation. CoRR abs/1805.09458 (2018) - [i48]Kyle Reing, Greg Ver Steeg, Aram Galstyan:
Maximizing Multivariate Information with Error-Correcting Codes. CoRR abs/1811.10839 (2018) - 2017
- [c50]Greg Ver Steeg, Rob Brekelmans, Hrayr Harutyunyan, Aram Galstyan:
Disentangled representations via synergy minimization. Allerton 2017: 180-187 - [c49]Linhong Zhu, Dong Guo, Junming Yin, Greg Ver Steeg, Aram Galstyan:
Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks (Extended Abstract). ICDE 2017: 57-58 - [c48]Greg Ver Steeg, Shuyang Gao, Kyle Reing, Aram Galstyan:
Sifting Common Information from Many Variables. IJCAI 2017: 2885-2892 - [i47]Hrayr Harutyunyan, Hrant Khachatrian, David C. Kale, Aram Galstyan:
Multitask Learning and Benchmarking with Clinical Time Series Data. CoRR abs/1703.07771 (2017) - [i46]Greg Ver Steeg, Aram Galstyan:
Low Complexity Gaussian Latent Factor Models and a Blessing of Dimensionality. CoRR abs/1706.03353 (2017) - [i45]Wenzhe Li, Dong Guo, Greg Ver Steeg, Aram Galstyan:
Unifying Local and Global Change Detection in Dynamic Networks. CoRR abs/1710.03035 (2017) - [i44]Greg Ver Steeg, Rob Brekelmans, Hrayr Harutyunyan, Aram Galstyan:
Disentangled Representations via Synergy Minimization. CoRR abs/1710.03839 (2017) - [i43]Armen E. Allahverdyan, Aram Galstyan:
Emergence of Leadership in Communication. CoRR abs/1710.09076 (2017) - [i42]Sahil Garg, Aram Galstyan, Irina Rish, Guillermo A. Cecchi, Shuyang Gao:
Efficient Representation for Natural Language Processing via Kernelized Hashcodes. CoRR abs/1711.04044 (2017) - [i41]Armen E. Allahverdyan, Greg Ver Steeg, Aram Galstyan:
Memory-induced mechanism for self-sustaining activity in networks. CoRR abs/1712.07844 (2017) - 2016
- [j10]V. S. Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer:
The DARPA Twitter Bot Challenge. Computer 49(6): 38-46 (2016) - [j9]Linhong Zhu, Dong Guo, Junming Yin, Greg Ver Steeg, Aram Galstyan:
Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks. IEEE Trans. Knowl. Data Eng. 28(10): 2765-2777 (2016) - [c47]Sahil Garg, Aram Galstyan, Ulf Hermjakob, Daniel Marcu:
Extracting Biomolecular Interactions Using Semantic Parsing of Biomedical Text. AAAI 2016: 2718-2726 - [c46]Jonathan Gordon, Linhong Zhu, Aram Galstyan, Prem Natarajan, Gully Burns:
Modeling Concept Dependencies in a Scientific Corpus. ACL (1) 2016 - [c45]Greg Ver Steeg, Aram Galstyan:
The Information Sieve. ICML 2016: 164-172 - [c44]Sarah K. Madsen, Greg Ver Steeg, Madelaine Daianu, Adam Mezher, Neda Jahanshad, Talia M. Nir, Xue Hua, Boris A. Gutman, Aram Galstyan, Paul M. Thompson:
Relative value of diverse brain MRI and blood-based biomarkers for predicting cognitive decline in the elderly. Medical Imaging: Image Processing 2016: 978411 - [c43]Shuyang Gao, Greg Ver Steeg, Aram Galstyan:
Variational Information Maximization for Feature Selection. NIPS 2016: 487-495 - [c42]Linhong Zhu, Majid Ghasemi-Gol, Pedro A. Szekely, Aram Galstyan, Craig A. Knoblock:
Unsupervised Entity Resolution on Multi-type Graphs. ISWC (1) 2016: 649-667 - [c41]Emilio Ferrara, Wen-Qiang Wang, Onur Varol, Alessandro Flammini, Aram Galstyan:
Predicting Online Extremism, Content Adopters, and Interaction Reciprocity. SocInfo (2) 2016: 22-39 - [c40]Yoon-Sik Cho, Greg Ver Steeg, Emilio Ferrara, Aram Galstyan:
Latent Space Model for Multi-Modal Social Data. WWW 2016: 447-458 - [i40]V. S. Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer, Rand Waltzman, Andrew Stevens, Alexander Dekhtyar, Shuyang Gao, Tad Hogg, Farshad Kooti, Yan Liu, Onur Varol, Prashant Shiralkar, V. G. Vinod Vydiswaran, Qiaozhu Mei, Tim Huang:
The DARPA Twitter Bot Challenge. CoRR abs/1601.05140 (2016) - [i39]Emilio Ferrara, Wen-Qiang Wang, Onur Varol, Alessandro Flammini, Aram Galstyan:
Predicting online extremism, content adopters, and interaction reciprocity. CoRR abs/1605.00659 (2016) - [i38]Greg Ver Steeg, Shuyang Gao, Kyle Reing, Aram Galstyan:
Sifting Common Information from Many Variables. CoRR abs/1606.02307 (2016) - [i37]Shuyang Gao, Greg Ver Steeg, Aram Galstyan:
Variational Information Maximization for Feature Selection. CoRR abs/1606.02827 (2016) - [i36]Kyle Reing, David C. Kale, Greg Ver Steeg, Aram Galstyan:
Toward Interpretable Topic Discovery via Anchored Correlation Explanation. CoRR abs/1606.07043 (2016) - 2015
- [c39]Shuyang Gao, Greg Ver Steeg, Aram Galstyan:
Efficient Estimation of Mutual Information for Strongly Dependent Variables. AISTATS 2015 - [c38]Greg Ver Steeg, Aram Galstyan:
Maximally Informative Hierarchical Representations of High-Dimensional Data. AISTATS 2015 - [c37]Sarah K. Madsen, Greg Ver Steeg, Adam Mezher, Neda Jahanshad, Talia M. Nir, Xue Hua, Boris A. Gutman, Aram Galstyan, Paul M. Thompson:
Information-theoretic characterization of blood panel predictors for brain atrophy and cognitive decline in the elderly. ISBI 2015: 980-984 - [c36]Madelaine Daianu, Greg Ver Steeg, Adam Mezher, Neda Jahanshad, Talia M. Nir, Xiaoran Yan, Gautam Prasad, Kristina Lerman, Aram Galstyan, Paul M. Thompson:
Information-Theoretic Clustering of Neuroimaging Metrics Related to Cognitive Decline in the Elderly. MCV@MICCAI 2015: 13-23 - [c35]Shuyang Gao, Greg Ver Steeg, Aram Galstyan:
Estimating Mutual Information by Local Gaussian Approximation. UAI 2015: 278-285 - [i35]Greg Ver Steeg, Aram Galstyan:
The Information Sieve. CoRR abs/1507.02284 (2015) - [i34]Shuyang Gao, Greg Ver Steeg, Aram Galstyan:
Estimating Mutual Information by Local Gaussian Approximation. CoRR abs/1508.00536 (2015) - [i33]Yoon-Sik Cho, Greg Ver Steeg, Emilio Ferrara, Aram Galstyan:
Latent Space Model for Multi-Modal Social Data. CoRR abs/1510.05318 (2015) - [i32]Sahil Garg, Aram Galstyan, Ulf Hermjakob, Daniel Marcu:
Extracting Biomolecular Interactions Using Semantic Parsing of Biomedical Text. CoRR abs/1512.01587 (2015) - 2014
- [j8]Vasanthan Raghavan, Greg Ver Steeg, Aram Galstyan, Alexander G. Tartakovsky:
Modeling Temporal Activity Patterns in Dynamic Social Networks. IEEE Trans. Comput. Soc. Syst. 1(1): 89-107 (2014) - [c34]Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan:
Where and Why Users "Check In". AAAI 2014: 269-275 - [c33]Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo:
Demystifying Information-Theoretic Clustering. ICML 2014: 19-27 - [c32]Greg Ver Steeg, Aram Galstyan:
Discovering Structure in High-Dimensional Data Through Correlation Explanation. NIPS 2014: 577-585 - [c31]Linhong Zhu, Aram Galstyan, James Cheng, Kristina Lerman:
Tripartite graph clustering for dynamic sentiment analysis on social media. SIGMOD Conference 2014: 1531-1542 - [r2]Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan:
Mixed Membership Blockmodels for Dynamic Networks with Feedback. Handbook of Mixed Membership Models and Their Applications 2014: 527-545 - [i31]Linhong Zhu, Aram Galstyan, James Cheng, Kristina Lerman:
Tripartite Graph Clustering for Dynamic Sentiment Analysis on Social Media. CoRR abs/1402.6010 (2014) - [i30]Greg Ver Steeg, Aram Galstyan:
Discovering Structure in High-Dimensional Data Through Correlation Explanation. CoRR abs/1406.1222 (2014) - [i29]Greg Ver Steeg, Aram Galstyan:
Maximally Informative Hierarchical Representations of High-Dimensional Data. CoRR abs/1410.7404 (2014) - [i28]Armen E. Allahverdyan, Aram Galstyan:
Active Inference for Binary Symmetric Hidden Markov Models. CoRR abs/1411.0630 (2014) - [i27]Shuyang Gao, Greg Ver Steeg, Aram Galstyan:
Efficient Estimation of Mutual Information for Strongly Dependent Variables. CoRR abs/1411.2003 (2014) - [i26]Linhong Zhu, Greg Ver Steeg, Aram Galstyan:
Scalable Link Prediction in Dynamic Networks via Non-Negative Matrix Factorization. CoRR abs/1411.3675 (2014) - [i25]Armen E. Allahverdyan, Aram Galstyan:
Opinion Dynamics with Confirmation Bias. CoRR abs/1411.4328 (2014) - [i24]Shuyang Gao, Greg Ver Steeg, Aram Galstyan:
Understanding confounding effects in linguistic coordination: an information-theoretic approach. CoRR abs/1412.0696 (2014) - 2013
- [j7]Aram Galstyan:
Continuous strategy replicator dynamics for multi-agent Q-learning. Auton. Agents Multi Agent Syst. 26(1): 37-53 (2013) - [c30]Greg Ver Steeg, Aram Galstyan:
Statistical Tests for Contagion in Observational Social Network Studies. AISTATS 2013: 563-571 - [c29]Vasanthan Raghavan, Greg Ver Steeg, Aram Galstyan, Alexander G. Tartakovsky:
Coupled hidden markov models for user activity in social networks. ICME Workshops 2013: 1-6 - [c28]Jihie Kim, Jae-Bong Yoo, Ho Lim, Huida Qiu, Zornitsa Kozareva, Aram Galstyan:
Sentiment Prediction Using Collaborative Filtering. ICWSM 2013 - [c27]Greg Ver Steeg, Aram Galstyan:
Information-theoretic measures of influence based on content dynamics. WSDM 2013: 3-12 - [r1]Aram Galstyan:
Activation Cascades in Structured Populations. Handbook of Human Computation 2013: 779-789 - [i23]Yoon-Sik Cho, Aram Galstyan, P. Jeffrey Brantingham, George E. Tita:
Latent Point Process Models for Spatial-Temporal Networks. CoRR abs/1302.2671 (2013) - [i22]Vasanthan Raghavan, Greg Ver Steeg, Aram Galstyan, Alexander G. Tartakovsky:
Modeling Temporal Activity Patterns in Dynamic Social Networks. CoRR abs/1305.1980 (2013) - [i21]Ardeshir Kianercy, Aram Galstyan:
Coevolutionary networks of reinforcement-learning agents. CoRR abs/1308.1049 (2013) - [i20]Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo:
Demystifying Information-Theoretic Clustering. CoRR abs/1310.4210 (2013) - [i19]Greg Ver Steeg, Cristopher Moore, Aram Galstyan, Armen E. Allahverdyan:
Phase Transitions in Community Detection: A Solvable Toy Model. CoRR abs/1312.0631 (2013) - [i18]Armen E. Allahverdyan, Aram Galstyan:
Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs. CoRR abs/1312.4551 (2013) - 2012
- [c26]Ardeshir Kianercy, Aram Galstyan, Armen E. Allahverdyan:
Adaptive agents on evolving networks. AAMAS 2012: 1391-1392 - [c25]Greg Ver Steeg, Aram Galstyan:
Information transfer in social media. WWW 2012: 509-518 - [i17]Vasanthan Raghavan, Aram Galstyan, Alexander G. Tartakovsky:
Hidden Markov Models for the Activity Profile of Terrorist Groups. CoRR abs/1207.1497 (2012) - [i16]Greg Ver Steeg, Aram Galstyan:
Inferring Predictive Links in Social Media Using Content Transfer. CoRR abs/1208.4475 (2012) - [i15]Greg Ver Steeg, Aram Galstyan:
Statistical Tests for Contagion in Observational Social Network Studies. CoRR abs/1211.4889 (2012) - 2011
- [c24]Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan:
Co-Evolution of Selection and Influence in Social Networks. AAAI 2011: 779-784 - [c23]Kristina Lerman, Aram Galstyan, Greg Ver Steeg, Tad Hogg:
Social Mechanics: An Empirically Grounded Science of Social Media. The Future of the Social Web 2011 - [c22]Armen E. Allahverdyan, Aram Galstyan:
Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs. NIPS 2011: 1674-1682 - [c21]Greg Ver Steeg, Aram Galstyan:
A Sequence of Relaxation Constraining Hidden Variable Models. UAI 2011: 717-726 - [c20]Greg Ver Steeg, Aram Galstyan, Armen E. Allahverdyan:
Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs (Abstract). UAI 2011: 853 - [i14]Aram Galstyan, Greg Ver Steeg, Armen E. Allahverdyan:
Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs. CoRR abs/1101.4227 (2011) - [i13]Greg Ver Steeg, Aram Galstyan:
A Sequence of Relaxations Constraining Hidden Variable Models. CoRR abs/1106.1636 (2011) - [i12]Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan:
Co-evolution of Selection and Influence in Social Networks. CoRR abs/1106.2788 (2011) - [i11]Aram Galstyan, Ardeshir Kianercy, Armen E. Allahverdyan:
Replicator Dynamics of Co-Evolving Networks. CoRR abs/1107.5354 (2011) - [i10]Ardeshir Kianercy, Aram Galstyan:
Dynamics of Softmax Q-Learning in Two-Player Two-Action Games. CoRR abs/1109.1528 (2011) - [i9]Greg Ver Steeg, Aram Galstyan:
Information Transfer in Social Media. CoRR abs/1110.2724 (2011) - 2010
- [c19]Aram Galstyan, Ardeshir Kianercy, Armen E. Allahverdyan:
Replicator Dynamics of Coevolving Networks. AAAI Fall Symposium: Complex Adaptive Systems 2010
2000 – 2009
- 2009
- [c18]Harris Chi Ho Chiu, Bo Ryu, Hua Zhu, Pedro A. Szekely, Rajiv T. Maheswaran, Craig Milo Rogers, Aram Galstyan, Behnam Salemi, Michael Rubenstein, Wei-Min Shen:
TENTACLES: Self-configuring robotic radio networks in unknown environments. IROS 2009: 1383-1388 - [c17]Armen E. Allahverdyan, Aram Galstyan:
On Maximum a Posteriori Estimation of Hidden Markov Processes. UAI 2009: 1-9 - [i8]Aram Galstyan:
Continuous Strategy Replicator Dynamics for Multi-Agent Learning. CoRR abs/0904.4717 (2009) - [i7]Aram Galstyan, Vahe L. Musoyan, Paul R. Cohen:
Maximizing Influence Propagation in Networks with Community Structure. CoRR abs/0905.1108 (2009) - [i6]Armen E. Allahverdyan, Aram Galstyan:
On Maximum a Posteriori Estimation of Hidden Markov Processes. CoRR abs/0906.1980 (2009) - [i5]Armen E. Allahverdyan, Aram Galstyan:
Community Detection with and without Prior Information. CoRR abs/0907.4803 (2009) - 2008
- [j6]Valentino Crespi, Aram Galstyan, Kristina Lerman:
Top-down vs bottom-up methodologies in multi-agent system design. Auton. Robots 24(3): 303-313 (2008) - [c16]Aram Galstyan, Paul R. Cohen:
Influence Propagation in Modular Networks. AAAI Spring Symposium: Social Information Processing 2008: 21-23 - [c15]Kristina Lerman, Aram Galstyan:
Analysis of social voting patterns on digg. WOSN 2008: 7-12 - [i4]Kristina Lerman, Aram Galstyan:
Analysis of Social Voting Patterns on Digg. CoRR abs/0806.1918 (2008) - 2007
- [c14]Aram Galstyan, Paul R. Cohen:
Empirical Comparison of "Hard" and "Soft" Label Propagation for Relational Classification. ILP 2007: 98-111 - 2006
- [j5]Kristina Lerman, Chris V. Jones, Aram Galstyan, Maja J. Mataric:
Analysis of Dynamic Task Allocation in Multi-Robot Systems. Int. J. Robotics Res. 25(3): 225-241 (2006) - [c13]Aram Galstyan, Paul R. Cohen:
Relational Classification Through Three-State Epidemic Dynamics. FUSION 2006: 1-7 - [c12]Aram Galstyan, Paul R. Cohen:
Iterative Relational Classification Through Three-State Epidemic Dynamics. ISI 2006: 83-92 - [i3]Aram Galstyan, Tad Hogg, Kristina Lerman:
Modeling and Mathematical Analysis of Swarms of Microscopic Robots. CoRR abs/cs/0604110 (2006) - [i2]Kristina Lerman, Chris V. Jones, Aram Galstyan, Maja J. Mataric:
Analysis of Dynamic Task Allocation in Multi-Robot Systems. CoRR abs/cs/0604111 (2006) - 2005
- [j4]Aram Galstyan, Karl Czajkowski, Kristina Lerman:
Resource Allocation in the Grid with Learning Agents. J. Grid Comput. 3(1-2): 91-100 (2005) - [c11]Valentino Crespi, Aram Galstyan, Kristina Lerman:
Comparative analysis of top-down and bottom-up methodologies for multi-agent system design. AAMAS 2005: 1159-1160 - [c10]Aram Galstyan, Paul R. Cohen:
Inferring Useful Heuristics from the Dynamics of Iterative Relational Classifiers. IJCAI 2005: 708-713 - [c9]Aram Galstyan, Tad Hogg, Kristina Lerman:
Modeling and mathematical analysis of swarms of microscopic robots. SIS 2005: 201-208 - 2004
- [j3]Wei-Min Shen, Peter M. Will, Aram Galstyan, Cheng-Ming Chuong:
Hormone-Inspired Self-Organization and Distributed Control of Robotic Swarms. Auton. Robots 17(1): 93-105 (2004) - [c8]Aram Galstyan, Kristina Lerman:
Analysis of a Stochastic Model of Adaptive Task Allocation in Robots. Engineering Self-Organising Systems 2004: 167-179 - [c7]Aram Galstyan, Karl Czajkowski, Kristina Lerman:
Resource Allocation in the Grid Using Reinforcement Learning. AAMAS 2004: 1314-1315 - [c6]Aram Galstyan, Bhaskar Krishnamachari, Kristina Lerman, Sundeep Pattem:
Distributed online localization in sensor networks using a moving target. IPSN 2004: 61-70 - [c5]Kristina Lerman, Alcherio Martinoli, Aram Galstyan:
A Review of Probabilistic Macroscopic Models for Swarm Robotic Systems. Swarm Robotics 2004: 143-152 - [i1]Kristina Lerman, Aram Galstyan, Tad Hogg:
Mathematical Analysis of Multi-Agent Systems. CoRR cs.RO/0404002 (2004) - 2003
- [c4]Aram Galstyan, Shashikiran Kolar, Kristina Lerman:
Resource allocation games with changing resource capacities. AAMAS 2003: 145-152 - [c3]Kristina Lerman, Aram Galstyan:
Agent memory and adaptation in multi-agent systems. AAMAS 2003: 797-803 - [c2]Alejandro Bugacov, Aram Galstyan, Kristina Lerman:
Threshold Behavior in a Boolean Network Model for SAT. IC-AI 2003: 87-92 - [c1]Kristina Lerman, Aram Galstyan:
Macroscopic analysis of adaptive task allocation in robots. IROS 2003: 1951-1956 - 2002
- [j2]Kristina Lerman, Aram Galstyan:
Mathematical Model of Foraging in a Group of Robots: Effect of Interference. Auton. Robots 13(2): 127-141 (2002) - 2001
- [j1]Kristina Lerman, Aram Galstyan, Alcherio Martinoli, Auke Jan Ijspeert:
A Macroscopic Analytical Model of Collaboration in Distributed Robotic Systems. Artif. Life 7(4): 375-393 (2001)
Coauthor Index
[c127] [c126] [c123] [i123] [c116] [c112] [c111] [c103] [c102] [i118] [i116] [i114] [i112] [i111] [j18] [c99] [c97] [c94] [c93] [c92] [i105] [i104] [i102] [i100] [j16] [j15] [c87] [c86] [c82] [c79] [c78] [c77] [c76] [i95] [i94] [i90] [i88] [i86] [i84] [i83] [i82] [j13] [c74] [c70] [c69] [i80] [i78] [i76] [i75] [i74] [i70] [i68] [c67] [c66] [c62] [c61] [c59] [c58] [i67] [i65] [i63] [i62] [i60] [c54] [c53] [c52] [i55] [i54] [i50] [i49] [i48] [c50] [c49] [c48] [i46] [i45] [i44] [i41] [j9] [c45] [c44] [c43] [c40] [i38] [i37] [i36] [c39] [c38] [c37] [c36] [c35] [i35] [i34] [i33] [j8] [c34] [c33] [c32] [r2] [i30] [i29] [i27] [i26] [i24] [c30] [c29] [c27] [i22] [i20] [i19] [c25] [i16] [i15] [c24] [c23] [c21] [c20] [i14] [i13] [i12] [i9]
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