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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 - [i52]Harshit Nigam, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
Acceleron: A Tool to Accelerate Research Ideation. CoRR abs/2403.04382 (2024) - [i51]Arushi Jain, Shubham Paliwal, Monika Sharma, Lovekesh Vig, Gautam Shroff:
SmartFlow: Robotic Process Automation using LLMs. CoRR abs/2405.12842 (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