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ORCIDGautam Shroff
Gautam M. Shroff
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- affiliation: Tata Consultancy Services Ltd., New Delhi, India
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2020 – today
- 2024
[c93]Aniruddha Mukherjee
, Rekha Singhal, Gautam Shroff:
Numin: Weighted-Majority Ensembles for Intraday Trading. ICAIF 2024: 703-710- [c92]Muskan Gupta, Priyanka Gupta, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
SCM4SR: Structural Causal Model-based Data Augmentation for Robust Session-based Recommendation. SIGIR 2024: 2609-2613 - [i53]Harshit Nigam, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
Acceleron: A Tool to Accelerate Research Ideation. CoRR abs/2403.04382 (2024) - [i52]Arushi Jain, Shubham Paliwal, Monika Sharma, Lovekesh Vig, Gautam Shroff:
SmartFlow: Robotic Process Automation using LLMs. CoRR abs/2405.12842 (2024) - [i51]Shubham Gandhi, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
BudgetMLAgent: A Cost-Effective LLM Multi-Agent system for Automating Machine Learning Tasks. CoRR abs/2411.07464 (2024) - 2023
- [c91]Shabbirhussain Bhaisaheb, Shubham Paliwal, Rajaswa Patil, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
Program Synthesis for Complex QA on Charts via Probabilistic Grammar Based Filtered Iterative Back-Translation. EACL (Findings) 2023: 2456-2470 - [c90]Jyoti Narwariya, Priyanka Gupta, Garima Gupta, Lovekesh Vig, Gautam Shroff:
X4SR: Post-Hoc Explanations for Session-based Recommendations. eCom@SIGIR 2023 - [c89]Omkar Nabar, Gautam Shroff:
Conservative Predictions on Noisy Financial Data. ICAIF 2023: 427-435 - [c88]Shrey Pandit, Gautam Shroff, Ashwin Srinivasan, Lovekesh Vig:
Can LLMs solve generative visual analogies? IARML@IJCAI 2023: 30-32 - [c87]Rishabh Patra, Ramya Hebbalaguppe, Tirtharaj Dash, Gautam Shroff, Lovekesh Vig:
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning. WACV 2023: 1541-1549 - [i50]S. I Harini, Gautam Shroff, Ashwin Srinivasan, Prayushi Faldu, Lovekesh Vig:
Neuro-symbolic Meta Reinforcement Learning for Trading. CoRR abs/2302.08996 (2023) - [i49]Aseem Arora, Shabbirhussain Bhaisaheb, Harshit Nigam, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
Adapt and Decompose: Efficient Generalization of Text-to-SQL via Domain Adapted Least-To-Most Prompting. CoRR abs/2308.02582 (2023) - [i48]Omkar Nabar, Gautam Shroff:
Conservative Predictions on Noisy Financial Data. CoRR abs/2310.11815 (2023) - 2022
- [c86]Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash:
Solving Visual Analogies Using Neural Algorithmic Reasoning (Student Abstract). AAAI 2022: 13055-13056 - [c85]Aditya Challa, Ashwin Srinivasan, Michael Bain, Gautam Shroff:
A Program-Synthesis Challenge for ARC-Like Tasks. ILP 2022: 25-39 - [c84]Vaibhav Varshney, Mayur Patidar, Rajat Kumar, Lovekesh Vig, Gautam Shroff:
Prompt Augmented Generative Replay via Supervised Contrastive Learning for Lifelong Intent Detection. NAACL-HLT (Findings) 2022: 1113-1127 - [c83]Rajat Kumar, Mayur Patidar, Vaibhav Varshney, Lovekesh Vig, Gautam Shroff:
Intent Detection and Discovery from User Logs via Deep Semi-Supervised Contrastive Clustering. NAACL-HLT 2022: 1836-1853 - [c82]Atharv Sonwane, Abhinav Lalwani, Sweta Mahajan, Gautam Shroff, Lovekesh Vig:
Neural Analogical Reasoning. NeSy 2022: 120-141 - [c81]Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan:
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces. NeSy 2022: 142-154 - [c80]Rajaswa Patil, Manasi Patwardhan, Shirish Karande, Lovekesh Vig, Gautam Shroff:
Exploring Dimensions of Generalizability and Few-shot Transfer for Text-to-SQL Semantic Parsing. TL4NLP 2022: 103-114 - [i47]Garima Gupta, Lovekesh Vig, Gautam Shroff:
DRTCI: Learning Disentangled Representations for Temporal Causal Inference. CoRR abs/2201.08137 (2022) - [i46]Diksha Garg, Pankaj Malhotra, Anil Bhatia, Sanjay Bhat, Lovekesh Vig, Gautam Shroff:
Learning to Liquidate Forex: Optimal Stopping via Adaptive Top-K Regression. CoRR abs/2202.12578 (2022) - [i45]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions. CoRR abs/2203.06852 (2022) - [i44]Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan:
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces. CoRR abs/2209.08750 (2022) - [i43]Vedant Shah, Aditya Agrawal, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Tanmay T. Verlekar:
Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss. CoRR abs/2211.16047 (2022) - [i42]Ramya Hebbalaguppe, Rishabh Patra, Tirtharaj Dash, Gautam Shroff, Lovekesh Vig:
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning. CoRR abs/2212.10005 (2022) - 2021
- [c79]Priyanka Gupta, Ankit Sharma, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
CauSeR: Causal Session-based Recommendations for Handling Popularity Bias. CIKM 2021: 3048-3052 - [c78]Saurabh Srivastava, Mayur Patidar, Sudip Chowdhury, Puneet Agarwal, Indrajit Bhattacharya, Gautam Shroff:
Complex Question Answering on knowledge graphs using machine translation and multi-task learning. EACL 2021: 3428-3439 - [c77]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions. ICDM 2021: 161-170 - [c76]Manasi Malik, Garima Gupta, Lovekesh Vig, Gautam Shroff:
BCQ4DCA: Budget Constrained Deep Q-Network for Dynamic Campaign Allocation in Computational Advertising. IJCNN 2021: 1-8 - [i41]Atharv Sonwane, Sharad Chitlangia, Tirtharaj Dash, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan:
Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems. CoRR abs/2110.09947 (2021) - [i40]Vedant Shah, Gautam Shroff:
Forecasting Market Prices using DL with Data Augmentation and Meta-learning: ARIMA still wins! CoRR abs/2110.10233 (2021) - [i39]Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash:
Solving Visual Analogies Using Neural Algorithmic Reasoning. CoRR abs/2111.10361 (2021) - 2020
- [j8]Priyanka Gupta, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis Using Deep Neural Networks. J. Heal. Informatics Res. 4(2): 112-137 (2020) - [j7]Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff:
Constructing generative logical models for optimisation problems using domain knowledge. Mach. Learn. 109(7): 1371-1392 (2020) - [c75]Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Vishnu TV:
Meta-Learning for Few-Shot Time Series Classification. COMAD/CODS 2020: 28-36 - [c74]Mouli Rastogi, Syed Afshan Ali, Mrinal Rawat, Lovekesh Vig, Puneet Agarwal, Gautam Shroff, Ashwin Srinivasan:
Information Extraction from Document Images via FCA based Template Detection and Knowledge Graph Rule Induction. CVPR Workshops 2020: 2377-2385 - [c73]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. ESANN 2020: 25-30 - [c72]Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
CAMTA: Causal Attention Model for Multi-touch Attribution. ICDM (Workshops) 2020: 79-86 - [c71]Saurabh Srivastava, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Vidya Vikas:
Capsule Based Neural Network Architecture to perform completeness check for Patent Eligibility Process. IJCNN 2020: 1-8 - [c70]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
Hi-CI: Deep Causal Inference in High Dimensions. CD@KDD 2020: 39-61 - [c69]Himani Srivastava, Prerna Khurana, Saurabh Srivastava, Vaibhav Varshney, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Improved Question Answering using Domain Prediction. Converse@KDD 2020 - [c68]Kushagra Mahajan, Monika Sharma, Lovekesh Vig, Rishab Khincha, Soundarya Krishnan, Adithya Niranjan, Tirtharaj Dash, Ashwin Srinivasan, Gautam Shroff:
CovidDiagnosis: Deep Diagnosis of COVID-19 Patients Using Chest X-Rays. TIA@MICCAI 2020: 61-73 - [c67]Shruti Kunde, Mayank Mishra, Amey Pandit, Rekha Singhal, Manoj Karunakaran Nambiar, Gautam Shroff, Shashank Gupta:
Recommending in changing times. RecSys 2020: 714-719 - [i38]Manish Shukla, Rajan M. A, Sachin Lodha, Gautam Shroff, Ramesh Raskar:
Privacy Guidelines for Contact Tracing Applications. CoRR abs/2004.13328 (2020) - [i37]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. CoRR abs/2004.13446 (2020) - [i36]Jyoti Narwariya, Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Gautam Shroff:
Graph Neural Networks for Leveraging Industrial Equipment Structure: An application to Remaining Useful Life Estimation. CoRR abs/2006.16556 (2020) - [i35]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Handling Variable-Dimensional Time Series with Graph Neural Networks. CoRR abs/2007.00411 (2020) - [i34]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
Hi-CI: Deep Causal Inference in High Dimensions. CoRR abs/2008.09858 (2020) - [i33]Diksha Garg, Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation. CoRR abs/2012.08984 (2020) - [i32]Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
CAMTA: Casual Attention Model for Multi-touch Attribution. CoRR abs/2012.11403 (2020)
2010 – 2019
- 2019
- [j6]Gautam Shroff, K. Ananth Krishnan:
Computing research at Tata Consultancy Services. Commun. ACM 62(11): 62-63 (2019) - [c66]Kaushal Paneri, Vishnu TV, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Regularizing Fully Convolutional Networks for Time Series Classification by Decorrelating Filters. AAAI 2019: 10003-10004 - [c65]Mayur Patidar, Surabhi Kumari, Manasi Patwardhan, Shirish Karande, Puneet Agarwal, Lovekesh Vig, Gautam Shroff:
From Monolingual to Multilingual FAQ Assistant using Multilingual Co-training. DeepLo@EMNLP-IJCNLP 2019: 115-123 - [c64]Richa Verma, Sarmimala Saikia, Harshad Khadilkar, Puneet Agarwal, Gautam Shroff, Ashwin Srinivasan:
A Reinforcement Learning Framework for Container Selection and Ship Load Sequencing in Ports. AAMAS 2019: 2250-2252 - [c63]Rekha Singhal, Gautam Shroff, Mukund Kumar, Sharod Roy Choudhury, Sanket Kadarkar, Rupinder Virk, Siddharth Verma, Vartika Tewari:
Fast Online 'Next Best Offers' using Deep Learning. COMAD/CODS 2019: 217-223 - [c62]Puneet Agarwal, Maya Ramanath, Gautam Shroff:
Retrieving Relationships from a Knowledge Graph for Question Answering. ECIR (1) 2019: 35-50 - [c61]Arijit Ukil, Pankaj Malhotra, Soma Bandyopadhyay, Tulika Bose, Ishan Sahu, Ayan Mukherjee, Lovekesh Vig, Arpan Pal, Gautam Shroff:
Fusing Features based on Signal Properties and TimeNet for Time Series Classification. ESANN 2019 - [c60]Kathan Kashiparekh, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification. IJCNN 2019: 1-8 - [c59]Saurabh Srivastava, Puneet Agarwal, Gautam Shroff, Lovekesh Vig:
Hierarchical Capsule Based Neural Network Architecture for Sequence Labeling. IJCNN 2019: 1-8 - [c58]Vishal Sunder, Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff, Rohit Rahul:
One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis. NeSy@IJCAI 2019 - [c57]Garima Gupta, Vishal Sunder, Ranjitha Prasad, Gautam Shroff:
CRESA: A Deep Learning Approach to Competing Risks, Recurrent Event Survival Analysis. PAKDD (2) 2019: 108-122 - [c56]Amit Sangroya, Pratik Saini, Mrinal Rawat, Gautam Shroff, C. Anantaram:
Natural Language Business Intelligence Question Answering Through SeqtoSeq Transfer Learning. PAKDD (Workshops) 2019: 286-297 - [c55]Vishnu TV, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Meta-Learning for Black-Box Optimization. ECML/PKDD (2) 2019: 366-381 - [c54]Diksha Garg, Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Sequence and Time Aware Neighborhood for Session-based Recommendations: STAN. SIGIR 2019: 1069-1072 - [i31]Vishnu TV, Diksha Garg, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models. CoRR abs/1903.09795 (2019) - [i30]Priyanka Gupta, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks. CoRR abs/1904.00655 (2019) - [i29]Kathan Kashiparekh, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification. CoRR abs/1904.12546 (2019) - [i28]Rekha Singhal, Gautam Shroff, Mukund Kumar, Sharod Roy Choudhury, Sanket Kadarkar, Rupinder Virk, Siddharth Verma, Vartika Tewari:
Fast Online "Next Best Offers" using Deep Learning. CoRR abs/1905.13368 (2019) - [i27]Vishal Sunder, Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff, Rohit Rahul:
One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis. CoRR abs/1906.02427 (2019) - [i26]Vishnu TV, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Meta-Learning for Black-box Optimization. CoRR abs/1907.06901 (2019) - [i25]Priyanka Gupta, Diksha Garg, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
NISER: Normalized Item and Session Representations with Graph Neural Networks. CoRR abs/1909.04276 (2019) - [i24]Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Vishnu TV:
Meta-Learning for Few-Shot Time Series Classification. CoRR abs/1909.07155 (2019) - [i23]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population. CoRR abs/1912.03960 (2019) - 2018
- [c53]Vishwanath D, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling. AAAI Workshops 2018: 699-705 - [c52]Vishwanath D, Rohit Rahul, Gunjan Sehgal, Swati, Arindam Chowdhury, Monika Sharma, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan:
Deep Reader: Information Extraction from Document Images via Relation Extraction and Natural Language. ACCV Workshops 2018: 186-201 - [c51]Mayur Patidar, Puneet Agarwal, Lovekesh Vig, Gautam Shroff:
Automatic Conversational Helpdesk Solution using Seq2Seq and Slot-filling Models. CIKM 2018: 1967-1975 - [c50]Karamjit Singh, Garima Gupta, Vartika Tewari, Gautam Shroff:
Comparative benchmarking of causal discovery algorithms. COMAD/CODS 2018: 46-56 - [c49]Sakti Saurav, Pankaj Malhotra, Vishnu TV, Narendhar Gugulothu, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Online anomaly detection with concept drift adaptation using recurrent neural networks. COMAD/CODS 2018: 78-87 - [c48]Sarmimala Saikia, Richa Verma, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan:
Evolutionary RL for Container Loading. ESANN 2018 - [c47]Mahesh P. Singh, Puneet Agarwal, Ashish Chaudhary, Gautam Shroff, Prerna Khurana, Mayur Patidar, Vivek Bisht, Rachit Bansal, Prateek Sachan, Rohit Kumar:
KNADIA: Enterprise KNowledge Assisted DIAlogue Systems Using Deep Learning. ICDE 2018: 1423-1434 - [c46]Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Using Features From Pre-trained TimeNET For Clinical Predictions. KDH@IJCAI 2018: 38-44 - [c45]Prerna Khurana, Puneet Agarwal, Gautam Shroff, Lovekesh Vig:
Resolving Abstract Anaphora Implicitly in Conversational Assistants using a Hierarchically stacked RNN. KDD 2018: 433-442 - [c44]Pravin Bhagwat, Andrea Goldsmith, Manish Gupta, Rajeev Rastogi, Gautam Shroff:
MobiCom'18 Panel: Hammer & Nail vis-a-vis AI / ML Applications to Networked Systems. MobiCom 2018: 653-654 - [c43]Gunjan Sehgal, Mrinal Rawat, Bindu Gupta, Garima Gupta, Geetika Sharma, Gautam Shroff:
Visual Predictive Analytics using iFuseML. EuroVA@EuroVis 2018: 13-17 - [i22]Sarmimala Saikia, Richa Verma, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan:
Evolutionary RL for Container Loading. CoRR abs/1805.06664 (2018) - [i21]Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks. CoRR abs/1807.01705 (2018) - [i20]Vishal Sunder, Lovekesh Vig, Arnab Chatterjee, Gautam Shroff:
Prosocial or Selfish? Agents with different behaviors for Contract Negotiation using Reinforcement Learning. CoRR abs/1809.07066 (2018) - [i19]Vishwanath D, Rohit Rahul, Gunjan Sehgal, Swati, Arindam Chowdhury, Monika Sharma, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan:
Deep Reader: Information extraction from Document images via relation extraction and Natural Language. CoRR abs/1812.04377 (2018) - [i18]Vishwanath D, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling. CoRR abs/1812.11158 (2018) - 2017
- [c42]Prerna Khurana, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan:
Hybrid BiLSTM-Siamese network for FAQ Assistance. CIKM 2017: 537-545 - [c41]Mohit Yadav, Lovekesh Vig, Gautam Shroff:
Learning and Knowledge Transfer with Memory Networks for Machine Comprehension. EACL (1) 2017: 850-859 - [c40]Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
TimeNet: Pre-trained deep recurrent neural network for time series classification. ESANN 2017 - [c39]Bindu Gupta, Kaushal Paneri, Gunjan Sehgal, Karamjit Singh, Geetika Sharma, Gautam Shroff:
Visual Statistical Analysis of Environmental Sensor Data. VAST 2017: 245-246 - [c38]Sunder Vishal, Mohit Yadav, Lovekesh Vig, Gautam Shroff:
Information Bottleneck Inspired Method For Chat Text Segmentation. IJCNLP(1) 2017: 194-203 - [c37]Karamjit Singh, Garima Gupta, Gautam Shroff, Puneet Agarwal:
Automated Product-Attribute Mapping. PAKDD (Workshops) 2017: 163-175 - [i17]Karamjit Singh, Garima Gupta, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
Deep Convolutional Neural Networks for Pairwise Causality. CoRR abs/1701.00597 (2017) - [i16]Karamjit Singh, Garima Gupta, Gautam Shroff, Puneet Agarwal:
Minimally-Supervised Attribute Fusion for Data Lakes. CoRR abs/1701.01094 (2017) - [i15]Kiran Sharma, Gunjan Sehgal, Bindu Gupta, Geetika Sharma, Arnab Chatterjee, Anirban Chakraborti, Gautam Shroff:
A complex network analysis of ethnic conflicts and human rights violations. CoRR abs/1705.03405 (2017) - [i14]Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
TimeNet: Pre-trained deep recurrent neural network for time series classification. CoRR abs/1706.08838 (2017) - [i13]Karamjit Singh, Garima Gupta, Vartika Tewari, Gautam Shroff:
Comparative Benchmarking of Causal Discovery Techniques. CoRR abs/1708.06246 (2017) - [i12]Narendhar Gugulothu, Vishnu TV, Pankaj Malhotra, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks. CoRR abs/1709.01073 (2017) - [i11]Gunjan Sehgal, Bindu Gupta, Kaushal Paneri, Karamjit Singh, Geetika Sharma, Gautam Shroff:
Crop Planning using Stochastic Visual Optimization. CoRR abs/1710.09077 (2017) - 2016
- [c36]Karamjit Singh, Kaushal Paneri, Aditeya Pandey, Garima Gupta, Geetika Sharma, Puneet Agarwal, Gautam Shroff:
Visual Bayesian fusion to navigate a data lake. FUSION 2016: 987-994 - [c35]Mayur Patidar, Shaurya Rohatgi, Ashish Chaudhary, Mahesh P. Singh, Puneet Agarwal, Gautam Shroff:
Activity Detection from Email Meta-Data Clustering. ICDM Workshops 2016: 568-575 - [c34]Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia:
Generation of Near-Optimal Solutions Using ILP-Guided Sampling. ILP 2016: 120-131 - [c33]Ramakrishna Perla, Ehtesham Hassan, Ramya Hebbalaguppe, Monika Sharma, Gaurav Gupta, Lovekesh Vig, Geetika Sharma, Gautam Shroff:
An AR Inspection Framework: Feasibility Study with Multiple AR Devices. ISMAR Adjunct 2016: 221-226 - [c32]Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Puneet Agarwal, Richa Rawat:
Neuro-Symbolic EDA-Based Optimization Using ILP-Enhanced DBNs. CoCo@NIPS 2016 - [c31]Auon Haidar Kazmi, Gautam Shroff, Puneet Agarwal:
Generic Framework to Predict Repeat Behavior of Customers Using Their Transaction History. WI 2016: 449-452 - [i10]Puneet Agarwal, Maya Ramanath, Gautam Shroff:
Relationship Queries on Large graphs using Pregel. CoRR abs/1605.00060 (2016) - [i9]Mohit Yadav, Pankaj Malhotra, Lovekesh Vig, K. Sriram, Gautam Shroff:
ODE - Augmented Training Improves Anomaly Detection in Sensor Data from Machines. CoRR abs/1605.01534 (2016) - [i8]Pankaj Malhotra, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection. CoRR abs/1607.00148 (2016) - [i7]Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia, Puneet Agarwal:
Generation of Near-Optimal Solutions Using ILP-Guided Sampling. CoRR abs/1608.01093 (2016) - [i6]Pankaj Malhotra, Vishnu TV, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Multi-Sensor Prognostics using an Unsupervised Health Index based on LSTM Encoder-Decoder. CoRR abs/1608.06154 (2016) - [i5]Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Puneet Agarwal, Richa Rawat:
Neuro-symbolic EDA-based Optimisation using ILP-enhanced DBNs. CoRR abs/1612.06528 (2016) - 2015
- [c30]Puneet Agarwal, Maya Ramanath, Gautam Shroff:
Distributed Algorithm for Relationship Queries on Large Graphs. LSDS-IR@CIKM 2015: 9-12 - [c29]Ehtesham Hassan, Gautam Shroff, Puneet Agarwal:
Multi-sensor event detection using shape histograms. CODS 2015: 20-29 - [c28]Puneet Agarwal, Gautam Shroff, Sarmimala Saikia, Zaigham Khan:
Efficiently discovering frequent motifs in large-scale sensor data. CODS 2015: 98-103 - [c27]Sarmimala Saikia, Gautam Shroff, Puneet Agarwal, Ashwin Srinivasan:
Succinctly summarizing machine usage via multi-subspace clustering of multi-sensor data. DSAA 2015: 1-10 - [c26]Karamjit Singh, Gautam Shroff, Puneet Agarwal:
Predictive reliability mining for early warnings in populations of connected machines. DSAA 2015: 1-10 - [c25]Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
Long Short Term Memory Networks for Anomaly Detection in Time Series. ESANN 2015 - [c24]Rahul Agrawal, Anirban Chakraborti, Karamjit Singh, Gautam Shroff, Venkatesh Sarangan:
Group-Based Pricing to Shape Demand in Real-Time Electricity Markets. EUMAS/AT 2015: 121-128 - [c23]Surya Yadav, Gautam Shroff, Ehtesham Hassan, Puneet Agarwal:
Business data fusion. FUSION 2015: 1876-1885 - [c22]Geetika Sharma, Gautam Shroff, Aditeya Pandey, Brijendra Singh, Gunjan Sehgal, Kaushal Paneri, Puneet Agarwal:
Multi-sensor Visual Analytics Supported by Machine-Learning Models. ICDM Workshops 2015: 668-674 - [i4]Puneet Agarwal, Gautam Shroff, Sarmimala Saikia, Zaigham Khan:
Efficiently Discovering Frequent Motifs in Large-scale Sensor Data. CoRR abs/1501.00405 (2015) - 2014
- [c21]Sarmimala Saikia, Gautam Shroff, Puneet Agarwal, Ashwin Srinivasan, Aditeya Pandey, Gaurangi Anand:
Exploratory Data Analysis Using Alternating Covers of Rules and Exceptions. COMAD 2014: 105-108 - [c20]Pankaj Malhotra, Puneet Agarwal, Gautam Shroff:
Graph-Parallel Entity Resolution using LSH & IMM. EDBT/ICDT Workshops 2014: 41-49 - [c19]Pankaj Malhotra, Puneet Agarwal, Gautam Shroff:
Incremental entity fusion from linked documents. FUSION 2014: 1-8 - [c18]Gautam Shroff, Puneet Agarwal, Karamjit Singh, Auon Haidar Kazmi, Sapan Shah, Avadhut Sardeshmukh:
Prescriptive information fusion. FUSION 2014: 1-8 - [c17]Geetika Sharma, Gautam Shroff, Aditeya Pandey, Puneet Agarwal, Ashwin Srinivasan:
Interactively Visualizing Summaries of Rules and Exceptions. EuroVA@EuroVis 2014 - [c16]Gautam Shroff, Lipika Dey, Hiranmay Ghosh:
Enterprise Contextual Intelligence. WI-IAT (1) 2014: 202-209 - [i3]Pankaj Malhotra, Puneet Agarwal, Gautam Shroff:
Incremental Entity Resolution from Linked Documents. CoRR abs/1402.4417 (2014) - [i2]Ehtesham Hassan, Gautam Shroff, Puneet Agarwal:
Multi-Sensor Event Detection using Shape Histograms. CoRR abs/1408.3733 (2014) - [i1]Karamjit Singh, Puneet Agarwal, Gautam Shroff:
Warranty Cost Estimation Using Bayesian Network. CoRR abs/1411.3197 (2014) - 2013
- [c15]Puneet Agarwal, Gautam Shroff, Pankaj Malhotra:
Approximate Incremental Big-Data Harmonization. BigData Congress 2013: 118-125 - [c14]Lipika Dey, Sameera Bharadwaja H., G. Meera, Gautam Shroff:
Email Analytics for Activity Management and Insight Discovery. Web Intelligence 2013: 557-564 - [e3]Sugata Ghosal, Gautam Shroff, Satish Chandra, Nachiappan Nagappan:
6th India Software Engineering Conference, ISEC '13, New Delhi, India - February 21 - 23, 2013. ACM 2013, ISBN 978-1-4503-1987-4 [contents] - 2012
- [c13]Puneet Agarwal, Rajgopal Vaithiyanathan, Saurabh Sharma, Gautam Shroff:
Catching the Long-Tail: Extracting Local News Events from Twitter. ICWSM 2012 - 2011
- [c12]Gautam Shroff, Puneet Agarwal, Lipika Dey:
Enterprise information fusion for real-time business intelligence. FUSION 2011: 1-8 - [c11]Gautam Shroff, Saurabh Sharma, Puneet Agarwal, Shefali Bhat:
A blackboard architecture for data-intensive information fusion using locality-sensitive hashing. FUSION 2011: 1-8 - [e2]Arun Bahulkar, K. Kesavasamy, T. V. Prabhakar, Gautam Shroff:
Proceeding of the 4th Annual India Software Engineering Conference, ISEC 2011, Thiruvananthapuram, Kerala, India, February 24-27, 2011. ACM 2011, ISBN 978-1-4503-0559-4 [contents] - 2010
- [c10]Prasun Dewan, Puneet Agarwal, Gautam Shroff, Rajesh Hegde:
Mixed-focus collaboration without compromising individual or group work. EICS 2010: 225-234
2000 – 2009
- 2009
- [c9]Prasun Dewan, Puneet Agarwal, Gautam Shroff, Rajesh Hegde:
Experiments in distributed side-by-side software development. CollaborateCom 2009: 1-10 - [c8]Prasun Dewan, Puneet Agarwal, Gautam Shroff, Rajesh Hegde:
Distributed side-by-side programming. CHASE 2009: 48-55 - [c7]Gautam Shroff, Puneet Agarwal, Premkumar T. Devanbu:
InstantApps: A WYSIWYG model driven interpreter for web applications. ICSE Companion 2009: 417-418 - [c6]Gautam Shroff, Puneet Agarwal, Premkumar T. Devanbu:
Instant multi-tier web applications without tears. ISEC 2009: 3-12 - 2008
- [c5]Gautam Shroff:
Dev 2.0: model driven development in the cloud. SIGSOFT FSE 2008: 283 - [e1]Gautam Shroff, Pankaj Jalote, Sriram K. Rajamani:
Proceeding of the 1st Annual India Software Engineering Conference, ISEC 2008, Hyderabad, India, February 19-22, 2008. ACM 2008, ISBN 978-1-59593-917-3 [contents] - 2006
- [j5]Pankaj Bhatt, Williams K, Gautam Shroff, Arun Kumar Misra:
Influencing factors in outsourced software maintenance. ACM SIGSOFT Softw. Eng. Notes 31(3): 1-6 (2006) - [j4]Pankaj Bhatt, Gautam Shroff, C. Anantaram, Arun Kumar Misra:
An influence model for factors in outsourced software maintenance. J. Softw. Maintenance Res. Pract. 18(6): 385-423 (2006) - [c4]Pankaj Bhatt, Gautam Shroff, K. Williams, Arun Kumar Misra:
An Empirical Study of Factors and their Relationships in Outsourced Software Maintenance. APSEC 2006: 301-308 - 2005
- [c3]Gautam Shroff, Anish Mehta, Puneet Agarwal, Rajesh Sinha:
Collaborative development of business applications. CollaborateCom 2005 - [c2]Abhiram Gandhe, Puneet Agarwal, Gautam Shroff:
JfelX: A Dynamic Model Driven Architecture. Software Engineering Research and Practice 2005: 382-388 - 2004
- [j3]Pankaj Bhatt, Gautam Shroff, Arun Kumar Misra:
Dynamics of software maintenance. ACM SIGSOFT Softw. Eng. Notes 29(5): 1-5 (2004)
1990 – 1999
- 1996
- [c1]Rekha Goel, Gautam M. Shroff:
Transparent parallel replication of logically partitioned databases. HiPC 1996: 132-137 - 1992
- [j2]Gautam M. Shroff, Christian H. Bischof:
Adaptive Condition Estimation for Rank-One Updates of QR Factorizations. SIAM J. Matrix Anal. Appl. 13(4): 1264-1278 (1992) - [j1]Christian H. Bischof, Gautam M. Shroff:
On updating signal subspaces. IEEE Trans. Signal Process. 40(1): 96-105 (1992)
Coauthor Index
[c78] [c74] [c71] [c69] [c65] [c64] [c62] [c59] [c53] [c51] [c49] [c48] [c47] [c45] [i22] [i18] [c42] [c40] [c37] [i17] [i16] [i14] [i12] [c36] [c35] [c32] [c31] [i10] [i8] [i7] [i6] [i5] [c30] [c29] [c28] [c27] [c26] [c25] [c23] [c22] [i4] [c21] [c20] [c19] [c18] [c17] [i3] [i2] [i1] [c15] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c3] [c2]
[c92] [i53] [i52] [i51] [c91] [c90] [c88] [c87] [i50] [i49] [c86] [c84] [c83] [c82] [c81] [c80] [i47] [i46] [i45] [i44] [i43] [i42] [c79] [c77] [c76] [i41] [i39] [j8] [j7] [c75] [c74] [c73] [c72] [c71] [c70] [c69] [c68] [i37] [i36] [i35] [i34] [i33] [i32] [c66] [c65] [c61] [c60] [c59] [c58] [c55] [c54] [i31] [i30] [i29] [i27] [i26] [i25] [i24] [i23] [c53] [c52] [c51] [c49] [c48] [c46] [c45] [i22] [i21] [i20] [i19] [i18] [c42] [c41] [c40] [c38] [i17] [i14] [i12] [c34] [c33] [c32] [i9] [i8] [i7] [i6] [i5] [c25]
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