Dubhashi, Devdatt

12 publications

NeurIPS 2024 Active Preference Learning for Ordering Items In- and Out-of-Sample Herman Bergström, Emil Carlsson, Devdatt Dubhashi, Fredrik D. Johansson

ICMLW 2024 Learning Efficient Recursive Numeral Systems via Reinforcement Learning Jonathan David Thomas, Andrea Silvi, Devdatt Dubhashi, Emil Carlsson, Moa Johansson

NeurIPSW 2024 PACE: Procedural Abstractions for Communicating Efficiently Jonathan David Thomas, Andrea Silvi, Devdatt Dubhashi, Vikas Garg, Moa Johansson

NeurIPS 2024 Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms Marc Wanner, Laura Lewis, Chiranjib Bhattacharyya, Devdatt Dubhashi, Alexandru Gheorghiu

AISTATS 2024 Pure Exploration in Bandits with Linear Constraints Emil Carlsson, Debabrota Basu, Fredrik Johansson, Devdatt Dubhashi

AISTATS 2023 Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves David Bosch, Ashkan Panahi, Ayca Ozcelikkale, Devdatt Dubhashi

ICML 2023 Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework Arman Rahbar, Ashkan Panahi, Morteza Haghir Chehreghani, Devdatt Dubhashi, Hamid Krim

ICML 2017 Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery Ashkan Panahi, Devdatt Dubhashi, Fredrik D. Johansson, Chiranjib Bhattacharyya

NeurIPS 2015 Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization Fredrik D Johansson, Ankani Chattoraj, Chiranjib Bhattacharyya, Devdatt Dubhashi

ICML 2014 Global Graph Kernels Using Geometric Embeddings Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi, Chiranjib Bhattacharyya

JMLR 2013 Lovasz Theta Function, SVMs and Finding Dense Subgraphs Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya, Devdatt Dubhashi

NeurIPS 2012 The Lovász Θ Function, SVMs and Finding Large Dense Subgraphs Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya, Devdatt Dubhashi