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Asish Ghoshal
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2020 – today
- 2023
- [c19]Minghan Li
, Sheng-Chieh Lin, Barlas Oguz, Asish Ghoshal, Jimmy Lin, Yashar Mehdad, Wen-tau Yih, Xilun Chen:
CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval. ACL (1) 2023: 11891-11907 - 2022
- [c18]Asish Ghoshal, Srinivasan Iyer, Bhargavi Paranjape, Kushal Lakhotia, Scott Wen-tau Yih, Yashar Mehdad:
QUASER: Question Answering with Scalable Extractive Rationalization. SIGIR 2022: 1208-1218 - [i13]Minghan Li, Sheng-Chieh Lin, Barlas Oguz, Asish Ghoshal, Jimmy Lin, Yashar Mehdad, Wen-tau Yih, Xilun Chen:
CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval. CoRR abs/2211.10411 (2022) - [i12]Asish Ghoshal, Arash Einolghozati, Ankit Arun, Haoran Li, Lili Yu, Yashar Mehdad, Scott Wen-tau Yih, Asli Celikyilmaz:
Improving Faithfulness of Abstractive Summarization by Controlling Confounding Effect of Irrelevant Sentences. CoRR abs/2212.09726 (2022) - 2021
- [c17]Yilun Zhou, Adithya Renduchintala, Xian Li, Sida Wang, Yashar Mehdad, Asish Ghoshal:
Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms. AISTATS 2021: 1486-1494 - [c16]Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Scott Yih, Yashar Mehdad, Srini Iyer:
FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation. EMNLP (1) 2021: 3712-3727 - [c15]Asish Ghoshal, Xilun Chen, Sonal Gupta, Luke Zettlemoyer, Yashar Mehdad:
Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing. ICLR 2021 - [i11]Yilun Zhou, Adi Renduchintala, Xian Li, Sida Wang, Yashar Mehdad, Asish Ghoshal:
Towards Understanding the Optimal Behaviors of Deep Active Learning Algorithms. CoRR abs/2101.00977 (2021) - 2020
- [c14]Kevin Bello, Asish Ghoshal, Jean Honorio
:
Minimax Bounds for Structured Prediction Based on Factor Graphs. AISTATS 2020: 213-222 - [c13]Xilun Chen, Asish Ghoshal, Yashar Mehdad, Luke Zettlemoyer, Sonal Gupta:
Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing. EMNLP (1) 2020: 5090-5100 - [i10]Xilun Chen, Asish Ghoshal, Yashar Mehdad, Luke Zettlemoyer, Sonal Gupta:
Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing. CoRR abs/2010.03546 (2020) - [i9]Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Wen-tau Yih, Yashar Mehdad, Srinivasan Iyer:
FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation. CoRR abs/2012.15482 (2020)
2010 – 2019
- 2019
- [i8]Kevin Bello, Asish Ghoshal, Jean Honorio:
Minimax bounds for structured prediction. CoRR abs/1906.00449 (2019) - 2018
- [j1]Asish Ghoshal, Jinyi Zhang, Michael A. Roth, Kevin Muyuan Xia, Ananth Y. Grama, Somali Chaterji
:
A Distributed Classifier for MicroRNA Target Prediction with Validation Through TCGA Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 15(4): 1037-1051 (2018) - [c12]Asish Ghoshal, Jean Honorio
:
Learning linear structural equation models in polynomial time and sample complexity. AISTATS 2018: 1466-1475 - [c11]Asish Ghoshal, Jean Honorio
:
Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity. AISTATS 2018: 1486-1494 - [c10]Asish Ghoshal, Jean Honorio
:
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time. ICML 2018: 1749-1757 - [i7]Asish Ghoshal, Jean Honorio:
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time. CoRR abs/1805.08196 (2018) - 2017
- [c9]Asish Ghoshal, Jean Honorio
:
Information-theoretic limits of Bayesian network structure learning. AISTATS 2017: 767-775 - [c8]Asish Ghoshal, Jean Honorio
:
Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions. AISTATS 2017: 1532-1540 - [c7]Asish Ghoshal, Jean Honorio:
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity. NIPS 2017: 6457-6466 - [i6]Asish Ghoshal, Jean Honorio:
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity. CoRR abs/1703.01196 (2017) - [i5]Asish Ghoshal, Jean Honorio:
Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions. CoRR abs/1703.01218 (2017) - [i4]Asish Ghoshal, Jean Honorio:
Learning Sparse Potential Games in Polynomial Time and Sample Complexity. CoRR abs/1706.05648 (2017) - [i3]Asish Ghoshal, Jean Honorio:
Learning linear structural equation models in polynomial time and sample complexity. CoRR abs/1707.04673 (2017) - 2016
- [c6]Asish Ghoshal, Jean Honorio
:
From behavior to sparse graphical games: Efficient recovery of equilibria. Allerton 2016: 1220-1227 - [c5]Nawanol Theera-Ampornpunt, Seong Gon Kim, Asish Ghoshal, Saurabh Bagchi, Ananth Grama, Somali Chaterji:
Fast training on large genomics data using distributed Support Vector Machines. COMSNETS 2016: 1-8 - [i2]Asish Ghoshal, Jean Honorio:
Information-theoretic lower bounds on learning the structure of Bayesian networks. CoRR abs/1601.07460 (2016) - [i1]Asish Ghoshal, Jean Honorio:
From Behavior to Sparse Graphical Games: Efficient Recovery of Equilibria. CoRR abs/1607.02959 (2016) - 2015
- [c4]Asish Ghoshal, Ananth Grama, Saurabh Bagchi, Somali Chaterji:
An ensemble SVM model for the accurate prediction of non-canonical MicroRNA targets. BCB 2015: 403-412 - 2013
- [c3]Asish Ghoshal, Dylan A. Shell:
Covering space with simple robots: From chains to random trees. ICRA 2013: 914-920 - 2012
- [c2]Asish Ghoshal, Avinash Parnandi, Robin R. Murphy:
Test method for measuring station-keeping with unmanned marine vehicles using sonar or optical sensors. PerMIS 2012: 155-159 - 2011
- [c1]Asish Ghoshal, Dylan A. Shell:
Being There, Being the RRT: Space-Filling and Searching in Place with Minimalist Robots. AAAI Spring Symposium: Multirobot Systems and Physical Data Structures 2011
Coauthor Index
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