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MADRaS : Multi Agent Driving Simulator

Oct 02, 2020
Anirban Santara, Sohan Rudra, Sree Aditya Buridi, Meha Kaushik, Abhishek Naik, Bharat Kaul, Balaraman Ravindran


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Reinforcement Learning for Improving Object Detection

Aug 18, 2020
Siddharth Nayak, Balaraman Ravindran

* 14 pages, 6 figures, 4 tables. Accepted in the RLQ-TOD workshop at ECCV 2020 

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A Causal Linear Model to Quantify Edge Unfairness for Unfair Edge Prioritization and Discrimination Removal

Jul 16, 2020
Pavan Ravishankar, Pranshu Malviya, Balaraman Ravindran

* Accepted in the Workshop on Law and Machine Learning, ICML 2020; First two authors contributed equally 

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Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement

Jul 06, 2020
Siddharth Nishtala, Harshavardhan Kamarthi, Divy Thakkar, Dhyanesh Narayanan, Anirudh Grama, Aparna Hegde, Ramesh Padmanabhan, Neha Madhiwalla, Suresh Chaudhary, Balaraman Ravindran, Milind Tambe


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Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains

Jun 07, 2020
Nazneen N Sultana, Hardik Meisheri, Vinita Baniwal, Somjit Nath, Balaraman Ravindran, Harshad Khadilkar


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On Incorporating Structural Information to improve Dialogue Response Generation

May 28, 2020
Nikita Moghe, Priyesh Vijayan, Balaraman Ravindran, Mitesh M. Khapra


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Understanding Dynamic Scenes using Graph Convolution Networks

May 15, 2020
Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K Madhava Krishna, Balaraman Ravindran, Anoop Namboodiri

* Under Review 

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Towards Transparent and Explainable Attention Models

Apr 29, 2020
Akash Kumar Mohankumar, Preksha Nema, Sharan Narasimhan, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran

* Accepted at ACL 2020 

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EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks

Apr 21, 2020
Sanchari Sen, Balaraman Ravindran, Anand Raghunathan

* Published as a conference paper at ICLR 2020 

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Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks

Feb 03, 2020
Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K Madhava Krishna, Balaraman Ravindran, Anoop Namboodiri


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SEERL: Sample Efficient Ensemble Reinforcement Learning

Jan 15, 2020
Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul


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Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems

Oct 01, 2019
Hardik Meisheri, Vinita Baniwal, Nazneen N Sultana, Balaraman Ravindran, Harshad Khadilkar

* 22 pages, 10 figures 

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Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning

Sep 09, 2019
Arjun Manoharan, Rahul Ramesh, Balaraman Ravindran


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Let's Ask Again: Refine Network for Automatic Question Generation

Aug 31, 2019
Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran

* accepted in EMNLP 2019 in Main Conference, (10 pages) 

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Learning policies for Social network discovery with Reinforcement learning

Jul 08, 2019
Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe


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ExTra: Transfer-guided Exploration

Jun 27, 2019
Anirban Santara, Rishabh Madan, Balaraman Ravindran, Pabitra Mitra

* Under review at NeurIPS 2019 

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Learning Interpretable Models Using an Oracle

Jun 17, 2019
Abhishek Ghose, Balaraman Ravindran


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MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning

May 17, 2019
Manan Tomar, Akhil Sathuluri, Balaraman Ravindran

* To appear in the Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019). (Extended Abstract) 

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Successor Options: An Option Discovery Framework for Reinforcement Learning

May 14, 2019
Rahul Ramesh, Manan Tomar, Balaraman Ravindran

* To appear in the proceedings of the International Joint Conference on Artificial Intelligence 2019 (IJCAI) 

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Optimal Resampling for Learning Small Models

May 04, 2019
Abhishek Ghose, Balaraman Ravindran


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Network Representation Learning: Consolidation and Renewed Bearing

May 02, 2019
Saket Gurukar, Priyesh Vijayan, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel, Balaraman Ravindran, Srinivasan Parthasarathy


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Polyphonic Music Composition with LSTM Neural Networks and Reinforcement Learning

Mar 03, 2019
Harish Kumar, Balaraman Ravindran


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An Active Learning Framework for Efficient Robust Policy Search

Jan 01, 2019
Sai Kiran Narayanaswami, Nandan Sudarsanam, Balaraman Ravindran

* 12 pages, 3 figures 

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Hypergraph Clustering: A Modularity Maximization Approach

Dec 28, 2018
Tarun Kumar, Sankaran Vaidyanathan, Harini Ananthapadmanabhan, Srinivasan Parthasarathy, Balaraman Ravindran


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Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning

Dec 26, 2018
Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran

* To appear in the Journal of Machine Vision and Applications, Springer. This work is an extended version of our previous work arXiv:1801.10447, "Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks", accepted at WACV 2018 

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Learning to Prevent Monocular SLAM Failure using Reinforcement Learning

Dec 23, 2018
Vignesh Prasad, Karmesh Yadav, Rohitashva Singh Saurabh, Swapnil Daga, Nahas Pareekutty, K. Madhava Krishna, Balaraman Ravindran, Brojeshwar Bhowmick

* Accepted in ICVGIP 2018. You can find more details on the project page at https://robotics.iiit.ac.in/people/vignesh.prasad/SLAMSafePlanner.html and in the video at https://www.youtube.com/watch?v=420QmM_Z8vo 

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