Highlights

Machine Learning and Interactive Intelligence

The topics include .

  1. Sangameshwar Patil, Balaraman Ravindran,
    Predicting software defect type using concept-based classification
    Empirical Software Engineering, 25, 2, 1341–1378, 2020.

  2. Abhishek Ghose, Balaraman Ravindran,
    Interpretability With Accurate Small Models
    Frontiers Artif. Intell., 3, 3, 2020.

  3. Nandan Sudarsanam, Nishanth Kumar, Abhishek Sharma, Balaraman Ravindran,
    Rate of change analysis for interestingness measures
    Knowl. Inf. Syst., 62, 1, 239–258, 2020.

  4. Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul,
    ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract)
    The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020, 13905–13906, 2020.

  5. Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe,
    Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling
    Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS ’20, Auckland, New Zealand, May 9-13, 2020, 575–583, 2020.

  6. Anirban Santara, Rishabh Madan, Pabitra Mitra, Balaraman Ravindran,
    ExTra: Transfer-guided Exploration
    Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS ’20, Auckland, New Zealand, May 9-13, 2020, 1987–1989, 2020.

  7. Sanchari Sen, Balaraman Ravindran, Anand Raghunathan,
    EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness Against Adversarial Attacks
    8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020, 2020.

  8. Anasua Mitra, Priyesh Vijayan, Srinivasan Parthasarathy, Balaraman Ravindran,
    A Unified Non-Negative Matrix Factorization Framework for Semi Supervised Learning on Graphs
    Proceedings of the 2020 SIAM International Conference on Data Mining, SDM 2020, Cincinnati, Ohio, USA, May 7-9, 2020 [the conference was canceled because of the coronavirus pandemic, the reviewed papers are published in this volume], 487–495, 2020.

  9. Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul,
    SEERL: Sample Efficient Ensemble Reinforcement Learning
    CoRR, abs/2001.05209, 2020.

  10. Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Balaraman Ravindran, Anoop Namboodiri,
    Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks
    CoRR, abs/2002.00786, 2020.

  11. Sanchari Sen, Balaraman Ravindran, Anand Raghunathan,
    EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks
    CoRR, abs/2004.10162, 2020.

  12. Akash Kumar Mohankumar, Preksha Nema, Sharan Narasimhan, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran,
    Towards Transparent and Explainable Attention Models
    CoRR, abs/2004.14243, 2020.

  13. Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Balaraman Ravindran, Anoop Namboodiri,
    Understanding Dynamic Scenes using Graph Convolution Networks
    CoRR, abs/2005.04437, 2020.

  14. Nikita Moghe, Priyesh Vijayan, Balaraman Ravindran, Mitesh M. Khapra,
    On Incorporating Structural Information to improve Dialogue Response Generation
    CoRR, abs/2005.14315, 2020.

  15. Nazneen N. Sultana, Hardik Meisheri, Vinita Baniwal, Somjit Nath, Balaraman Ravindran, Harshad Khadilkar,
    Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains
    CoRR, abs/2006.04037, 2020.

  16. Siddharth Nishtala, Harshavardhan Kamarthi, Divy Thakkar, Dhyanesh Narayanan, Anirudh Grama, Ramesh Padmanabhan, Neha Madhiwalla, Suresh Chaudhary, Balaraman Ravindran, Milind Tambe,
    Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement
    CoRR, abs/2006.07590, 2020.

  17. Nitesh Methani, Pritha Ganguly, Mitesh M. Khapra, Pratyush Kumar,
    PlotQA: Reasoning over Scientific Plots
    IEEE Winter Conference on Applications of Computer Vision, WACV 2020, Snowmass Village, CO, USA, March 1-5, 2020, 1516–1525, 2020.

  18. Pratyush Kumar, Muktabh Mayank Srivastava,
    Compact retail shelf segmentation for mobile deployment
    CoRR, abs/2004.13094, 2020.

  19. Anoop Kunchukuttan, Divyanshu Kakwani, Satish Golla, Gokul N. C., Avik Bhattacharyya, Mitesh M. Khapra, Pratyush Kumar,
    AI4Bharat-IndicNLP Corpus: Monolingual Corpora and Word Embeddings for Indic Languages
    CoRR, abs/2005.00085, 2020.

  20. Dev Yashpal Sheth, Arun Rajkumar,
    Active Ranking from Pairwise Comparisons with Dynamically Arriving Items and Voters
    CoDS-COMAD 2020: 7th ACM IKDD CoDS and 25th COMAD, Hyderabad India, January 5-7, 2020, 229–233, 2020.

  21. Sahil Manchanda, Arun Rajkumar, Simarjot Kaur, Narayanan Unny,
    SUPAID: A Rule mining based method for automatic rollout decision aid for supervisors in fleet management systems
    CoRR, abs/2001.03386, 2020.

  22. Saurabh Desai, Harish G. Ramaswamy,
    Ablation-CAM: Visual Explanations for Deep Convolutional Network via Gradient-free Localization
    IEEE Winter Conference on Applications of Computer Vision, WACV 2020, Snowmass Village, CO, USA, March 1-5, 2020, 972–980, 2020.

  23. Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran,
    Studying the plasticity in deep convolutional neural networks using random pruning
    Mach. Vis. Appl., 30, 2, 203–216, 2019.

  24. Manan Tomar, Akhil Sathuluri, Balaraman Ravindran,
    MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning
    The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, 10053–10054, 2019.

  25. Sai Kiran Narayanaswami, Balaraman Ravindran, Venkatesh Ramaiyan,
    Generalized random Surfer-Pair models
    ASONAM ’19: International Conference on Advances in Social Networks Analysis and Mining, Vancouver, British Columbia, Canada, 27-30 August, 2019, 452–455, 2019.

  26. Vaibhav Gupta, Daksh Anand, Praveen Paruchuri, Balaraman Ravindran,
    Advice Replay Approach for Richer Knowledge Transfer in Teacher Student Framework
    Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS ’19, Montreal, QC, Canada, May 13-17, 2019, 1997–1999, 2019.

  27. Manan Tomar, Akhil Sathuluri, Balaraman Ravindran,
    MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning
    Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS ’19, Montreal, QC, Canada, May 13-17, 2019, 2226–2228, 2019.

  28. Athindran Ramesh Kumar, Balaraman Ravindran, Anand Raghunathan,
    Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest Packing
    Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, COMAD/CODS 2019, Kolkata, India, January 3-5, 2019, 150–156, 2019.

  29. Tarun Kumar, Sankaran Vaidyanathan, Harini Ananthapadmanabhan, Srinivasan Parthasarathy, Balaraman Ravindran,
    A New Measure of Modularity in Hypergraphs: Theoretical Insights and Implications for Effective Clustering
    Complex Networks and Their Applications VIII - Volume 1 Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019, Lisbon, Portugal, December 10-12, 2019, 286–297, 2019.

  30. Manju Manohar Manjalavil, Gitakrishnan Ramadurai, Balaraman Ravindran,
    Temporal Analysis of a Bus Transit Network
    Complex Networks and Their Applications VIII - Volume 2 Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019, Lisbon, Portugal, December 10-12, 2019, 944–954, 2019.

  31. Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran,
    Let’s Ask Again: Refine Network for Automatic Question Generation
    Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3-7, 2019, 3312–3321, 2019.

  32. Rahul Ramesh, Manan Tomar, Balaraman Ravindran,
    Successor Options: An Option Discovery Framework for Reinforcement Learning
    Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, 3304–3310, 2019.

  33. Revanth Reddy, Sarath Chandar, Balaraman Ravindran,
    Edge Replacement Grammars : A Formal Language Approach for Generating Graphs
    Proceedings of the 2019 SIAM International Conference on Data Mining, SDM 2019, Calgary, Alberta, Canada, May 2-4, 2019, 351–359, 2019.

  34. Sai Kiran Narayanaswami, Nandan Sudarsanam, Balaraman Ravindran,
    An Active Learning Framework for Efficient Robust Policy Search
    CoRR, abs/1901.00117, 2019.

  35. Harish Kumar, Balaraman Ravindran,
    Polyphonic Music Composition with LSTM Neural Networks and Reinforcement Learning
    CoRR, abs/1902.01973, 2019.

  36. Revanth Reddy, Sarath Chandar, Balaraman Ravindran,
    Edge Replacement Grammars: A Formal Language Approach for Generating Graphs
    CoRR, abs/1902.07159, 2019.

  37. Saket Gurukar, Priyesh Vijayan, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel, Balaraman Ravindran, Srinivasan Parthasarathy,
    Network Representation Learning: Consolidation and Renewed Bearing
    CoRR, abs/1905.00987, 2019.

  38. Abhishek Ghose, Balaraman Ravindran,
    Optimal Resampling for Learning Small Models
    CoRR, abs/1905.01520, 2019.

  39. Rahul Ramesh, Manan Tomar, Balaraman Ravindran,
    Successor Options: An Option Discovery Framework for Reinforcement Learning
    CoRR, abs/1905.05731, 2019.

  40. Manan Tomar, Akhil Sathuluri, Balaraman Ravindran,
    MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning
    CoRR, abs/1905.07193, 2019.

  41. Abhishek Ghose, Balaraman Ravindran,
    Learning Interpretable Models Using an Oracle
    CoRR, abs/1906.06852, 2019.

  42. Anirban Santara, Rishabh Madan, Balaraman Ravindran, Pabitra Mitra,
    ExTra: Transfer-guided Exploration
    CoRR, abs/1906.11785, 2019.

  43. Sai Kiran Narayanaswami, Balaraman Ravindran, Venkatesh Ramaiyan,
    Generalized Random Surfer-Pair Models
    CoRR, abs/1907.01420, 2019.

  44. Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe,
    Learning policies for Social network discovery with Reinforcement learning
    CoRR, abs/1907.11625, 2019.

  45. Arjun Manoharan, Rahul Ramesh, Balaraman Ravindran,
    Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning
    CoRR, abs/1909.04134, 2019.

  46. Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran,
    Let’s Ask Again: Refine Network for Automatic Question Generation
    CoRR, abs/1909.05355, 2019.

  47. Hardik Meisheri, Vinita Baniwal, Nazneen N. Sultana, Balaraman Ravindran, Harshad Khadilkar,
    Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems
    CoRR, abs/1910.00211, 2019.

  48. Suman Banerjee, Mitesh M. Khapra,
    Graph Convolutional Network with Sequential Attention for Goal-Oriented Dialogue Systems
    Trans. Assoc. Comput. Linguistics, 7, 485–500, 2019.

  49. V. Rudra Murthy, Mitesh M. Khapra, Pushpak Bhattacharyya,
    Improving NER Tagging Performance in Low-Resource Languages via Multilingual Learning
    ACM Trans. Asian Low Resour. Lang. Inf. Process., 18, 2, 9:1–9:20, 2019.

  50. Ananya B. Sai, Mithun Das Gupta, Mitesh M. Khapra, Mukundhan Srinivasan,
    Re-Evaluating ADEM: A Deeper Look at Scoring Dialogue Responses
    The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, 6220–6227, 2019.

  51. Shweta Bhardwaj, Mukundhan Srinivasan, Mitesh M. Khapra,
    Efficient Video Classification Using Fewer Frames
    IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019, 354–363, 2019.

  52. Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran,
    Let’s Ask Again: Refine Network for Automatic Question Generation
    Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3-7, 2019, 3312–3321, 2019.

  53. Revanth Reddy, Rahul Ramesh, Ameet Deshpande, Mitesh M. Khapra,
    FigureNet : A Deep Learning model for Question-Answering on Scientific Plots
    International Joint Conference on Neural Networks, IJCNN 2019 Budapest, Hungary, July 14-19, 2019, 1–8, 2019.

  54. Siddhartha Arora, Mitesh M. Khapra, Harish G. Ramaswamy,
    On Knowledge distillation from complex networks for response prediction
    Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, Minneapolis, MN, USA, June 2-7, 2019, Volume 1 (Long and Short Papers), 3813–3822, 2019.

  55. Ananya Sai, Mithun Das Gupta, Mitesh M. Khapra, Mukundhan Srinivasan,
    Re-evaluating ADEM: A Deeper Look at Scoring Dialogue Responses
    CoRR, abs/1902.08832, 2019.

  56. Shweta Bhardwaj, Mukundhan Srinivasan, Mitesh M. Khapra,
    Efficient Video Classification Using Fewer Frames
    CoRR, abs/1902.10640, 2019.

  57. Soham Parikh, Ananya B. Sai, Preksha Nema, Mitesh M. Khapra,
    ElimiNet: A Model for Eliminating Options for Reading Comprehension with Multiple Choice Questions
    CoRR, abs/1904.02651, 2019.

  58. Soham Parikh, Ananya B. Sai, Preksha Nema, Mitesh M. Khapra,
    Frustratingly Poor Performance of Reading Comprehension Models on Non-adversarial Examples
    CoRR, abs/1904.02665, 2019.

  59. Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran,
    Let’s Ask Again: Refine Network for Automatic Question Generation
    CoRR, abs/1909.05355, 2019.

  60. Sahana Ramnath, Amrita Saha, Soumen Chakrabarti, Mitesh M. Khapra,
    Scene Graph based Image Retrieval - A case study on the CLEVR Dataset
    CoRR, abs/1911.00850, 2019.

  61. Rehan Ahmed, Bernhard Buchli, Stefan Draskovic, Lukas Sigrist, Pratyush Kumar, Lothar Thiele,
    Optimal Power Management with Guaranteed Minimum Energy Utilization for Solar Energy Harvesting Systems
    ACM Trans. Embedded Comput. Syst., 18, 4, 30:1–30:26, 2019.

  62. Mohit Jain, Rohun Tripathi, Ishita Bhansali, Pratyush Kumar,
    Automatic Generation and Evaluation of Usable and Secure Audio reCAPTCHA
    The 21st International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2019, Pittsburgh, PA, USA, October 28-30, 2019, 355–366, 2019.

  63. Naveen E, Pratyush Kumar,
    Checkpointing in Practice for Memory-Efficient Training on the Edge
    21st IEEE International Conference on High Performance Computing and Communications; 17th IEEE International Conference on Smart City; 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019, Zhangjiajie, China, August 10-12, 2019, 2759–2766, 2019.

  64. Nitesh Methani, Pritha Ganguly, Mitesh M. Khapra, Pratyush Kumar,
    Data Interpretation over Plots
    CoRR, abs/1909.00997, 2019.

  65. Himanshu Sharad Bhatt, Shourya Roy, Arun Rajkumar, Sriranjani Ramakrishnan,
    Learning Transferable Feature Representations Using Neural Networks
    Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28- August 2, 2019, Volume 1: Long Papers, 4124–4134, 2019.

  66. Prateek Yadav, Madhav Nimishakavi, Naganand Yadati, Shikhar Vashishth, Arun Rajkumar, Partha Pratim Talukdar,
    Lovasz Convolutional Networks
    The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan, 1978–1987, 2019.

  67. Arun Verma, Manjesh K. Hanawal, Arun Rajkumar, Raman Sankaran,
    Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback
    Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14 December 2019, Vancouver, BC, Canada, 14499–14509, 2019.

  68. Arun Verma, Manjesh K. Hanawal, Arun Rajkumar, Raman Sankaran,
    Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback
    CoRR, abs/1909.01504, 2019.

  69. Siddhartha Arora, Mitesh M. Khapra, Harish G. Ramaswamy,
    On Knowledge distillation from complex networks for response prediction
    Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, Minneapolis, MN, USA, June 2-7, 2019, Volume 1 (Long and Short Papers), 3813–3822, 2019.