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Budhiraja, A and Sukhwani, M and Aggarwal, M and Shevade, S and Sathyanarayana, G and Tallamraju, RB (2022) Using Relational Graph Convolutional Networks to Assign Fashion Communities to Users. In: 3rd workshop on recommender systems in fashion and retail, 2021, 27 September - 1 October 2021, Amsterdam, pp. 3-13.
Bharadwaj, S and Shevade, S (2022) Efficient Constituency Tree based Encoding for Natural Language to Bash Translation. In: 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022, 10 - 15 July 2022, Seattle, pp. 3159-3168.
Vijaikumar, M and Shevade, S and Murty, MN (2021) GRAM-SMOT: Top-N Personalized Bundle Recommendation via Graph Attention Mechanism and Submodular Optimization. In: European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, 14-18 Sep 2020, pp. 297-313.
Vijaikumar, M and Hada, D and Shevade, S (2021) HyperTeNet: Hypergraph and Transformer-based Neural Network for Personalized List Continuation. In: 21st IEEE International Conference on Data Mining, ICDM 2021, 7-10 Dec 2021, Virtual, Online, pp. 1210-1215.
Vijaikumar, M and Shevade, S and Murty, MN (2021) Neural Cross-Domain Collaborative Filtering with Shared Entities. In: European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, 14-18 Sep 2020, pp. 729-745.
Pal, S and Gupta, Y and Shukla, A and Kanade, A and Shevade, S and Ganapathy, V (2020) ACTIVETHIEF: Model extraction using active learning and unannotated public data. In: AAAI 2020 - 34th AAAI Conference on Artificial Intelligence, 7 - 12 February 2020, New York, pp. 865-872.
Vijaikumar, M and Shevade, S and Narasimha Murty, M (2020) GAMMA: A Graph and Multi-view Memory Attention Mechanism for Top-N Heterogeneous Recommendation. In: 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 11-14 May 2020, Singapore, pp. 28-40.
Vijaikumar, M and Shevade, S and Murty, MN (2020) SoRecGAT: Leveraging Graph Attention Mechanism for Top-N Social Recommendation. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2019, 16-20 September 2019, Wurzburg; Germany, pp. 430-446.
Vijaikumar, M and Shevade, S and Murty, MN (2019) TagEmbedSVD: Leveraging Tag Embeddings for Cross-Domain Collaborative Filtering. In: 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, 17 - 20 December 2019, Tezpur, pp. 240-248.
Gupta, R and Kanade, A and Shevade, S (2019) Deep reinforcement learning for syntactic error repair in student programs. In: 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, 27 January - 1 February 2019, Honolulu, pp. 930-937.
Gupta, R and Kanade, A and Shevade, S (2019) Neural attribution for semantic bug-localization in student programs. In: 33rd Annual Conference on Neural Information Processing Systems, NeurIPS 2019, 8-14 December 2019, Vancouver; Canada.
Rastogi, I and Kanade, A and Shevade, S (2018) Active learning for efficient testing of student programs. In: 19th International Conference on Artificial Intelligence in Education, AIED 2018, 27 - 30 June 2018, London, pp. 296-300.
Deepak, P and Garg, D and Shevade, S (2017) Latent space embedding for retrieval in question-answer archives. In: 2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017, 9 - 11 September 2017, Copenhagen, pp. 855-865.
Gupta, R and Pal, S and Kanade, A and Shevade, S (2017) DeepFix: Fixing Common C language errors by deep learning. In: 31st AAAI Conference on Artificial Intelligence, AAAI 2017, 4 - 10 February 2017, San Francisco, pp. 1345-1351.
Padmanabhan, D and Bhat, S and Prabuchandran, KJ and Shevade, S and Narahari, Y (2022) Dominant strategy truthful, deterministic multi-armed bandit mechanisms with logarithmic regret for sponsored search auctions. In: Applied Intelligence, 52 (3). pp. 3209-3226.
Padmanabhan, D and Bhat, S and Shevade, S and Narahari, Y (2017) Multi-label classification from multiple noisy sources using topic models. In: Information (Switzerland), 8 (2).
