Kumar, M. Pawan

51 publications

ICLR 2025 Do as I Do (Safely): Mitigating Task-Specific Fine-Tuning Risks in Large Language Models Francisco Eiras, Aleksandar Petrov, Philip Torr, M. Pawan Kumar, Adel Bibi

ICML 2024 Efficient Error Certification for Physics-Informed Neural Networks Francisco Eiras, Adel Bibi, Rudy R Bunel, Krishnamurthy Dj Dvijotham, Philip Torr, M. Pawan Kumar

ICLR 2024 Expressive Losses for Verified Robustness via Convex Combinations Alessandro De Palma, Rudy R Bunel, Krishnamurthy Dj Dvijotham, M. Pawan Kumar, Robert Stanforth, Alessio Lomuscio

ICMLW 2024 Mimicking User Data: On Mitigating Fine-Tuning Risks in Closed Large Language Models Francisco Eiras, Aleksandar Petrov, Philip Torr, M. Pawan Kumar, Adel Bibi

JMLR 2024 Scaling the Convex Barrier with Sparse Dual Algorithms Alessandro De Palma, Harkirat Singh Behl, Rudy Bunel, Philip H.S. Torr, M. Pawan Kumar

JMLR 2022 A Stochastic Bundle Method for Interpolation Alasdair Paren, Leonard Berrada, Rudra P. K. Poudel, M. Pawan Kumar

TMLR 2022 ANCER: Anisotropic Certification via Sample-Wise Volume Maximization Francisco Eiras, Motasem Alfarra, Philip Torr, M. Pawan Kumar, Puneet K. Dokania, Bernard Ghanem, Adel Bibi

TMLR 2022 Faking Interpolation Until You Make It Alasdair Paren, Rudra P. K. Poudel, M. Pawan Kumar

TMLR 2022 Lookback for Learning to Branch Prateek Gupta, Elias Boutros Khalil, Didier Chételat, Maxime Gasse, Andrea Lodi, Yoshua Bengio, M. Pawan Kumar

UAI 2021 Generating Adversarial Examples with Graph Neural Networks Florian Jaeckle, M. Pawan Kumar

NeurIPS 2021 Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications Leonard Berrada, Sumanth Dathathri, Krishnamurthy Dvijotham, Robert Stanforth, Rudy R Bunel, Jonathan Uesato, Sven Gowal, M. Pawan Kumar

NeurIPS 2021 Overcoming the Convex Barrier for Simplex Inputs Harkirat Singh Behl, M. Pawan Kumar, Philip Torr, Krishnamurthy Dvijotham

ICLR 2021 Scaling the Convex Barrier with Active Sets Alessandro De Palma, Harkirat Behl, Rudy R Bunel, Philip Torr, M. Pawan Kumar

JMLR 2020 Branch and Bound for Piecewise Linear Neural Network Verification Rudy Bunel, Jingyue Lu, Ilker Turkaslan, Philip H.S. Torr, Pushmeet Kohli, M. Pawan Kumar

ICLR 2020 Neural Network Branching for Neural Network Verification Jingyue Lu, M. Pawan Kumar

ICML 2020 Training Neural Networks for and by Interpolation Leonard Berrada, Andrew Zisserman, M. Pawan Kumar

ECCV 2020 Weakly Supervised Instance Segmentation by Learning Annotation Consistent Instances Aditya Arun, C.V. Jawahar, M. Pawan Kumar

ICLR 2019 A Statistical Approach to Assessing Neural Network Robustness Stefan Webb, Tom Rainforth, Yee Whye Teh, M. Pawan Kumar

ICLR 2019 Deep Frank-Wolfe for Neural Network Optimization Leonard Berrada, Andrew Zisserman, M. Pawan Kumar

AISTATS 2018 Learning to Round for Discrete Labeling Problems Pritish Mohapatra, C. V. Jawahar, M. Pawan Kumar

AISTATS 2018 Optimal Submodular Extensions for Marginal Estimation Pankaj Pansari, Chris Russell, M. Pawan Kumar

ICLR 2018 Smooth Loss Functions for Deep Top-K Classification Leonard Berrada, Andrew Zisserman, M. Pawan Kumar

CVPR 2017 Efficient Linear Programming for Dense CRFs Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar

ICLR 2017 Learning to Superoptimize Programs Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli

CVPR 2017 Truncated Max-of-Convex Models Pankaj Pansari, M. Pawan Kumar

ICLR 2017 Trusting SVM for Piecewise Linear CNNs Leonard Berrada, Andrew Zisserman, M. Pawan Kumar

ECCV 2016 Efficient Continuous Relaxations for Dense CRF Alban Desmaison, Rudy Bunel, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar

ECCV 2016 Partial Linearization Based Optimization for Multi-Class SVM Pritish Mohapatra, Puneet Kumar Dokania, C. V. Jawahar, M. Pawan Kumar

JMLR 2016 Rounding-Based Moves for Semi-Metric Labeling M. Pawan Kumar, Puneet K. Dokania

ICCV 2015 Entropy-Based Latent Structured Output Prediction Diane Bouchacourt, Sebastian Nowozin, M. Pawan Kumar

ICCV 2015 Parsimonious Labeling Puneet K. Dokania, M. Pawan Kumar

NeurIPS 2014 Efficient Optimization for Average Precision SVM Pritish Mohapatra, C.V. Jawahar, M. Pawan Kumar

ECCV 2014 Learning to Rank Using High-Order Information Puneet Kumar Dokania, Aseem Behl, C. V. Jawahar, M. Pawan Kumar

CVPR 2014 Optimizing Average Precision Using Weakly Supervised Data Aseem Behl, C. V. Jawahar, M. Pawan Kumar

NeurIPS 2014 Rounding-Based Moves for Metric Labeling M. Pawan Kumar

AISTATS 2012 Max-Margin Min-Entropy Models Kevin Miller, M. Pawan Kumar, Ben Packer, Danny Goodman, Daphne Koller

ICML 2012 Modeling Latent Variable Uncertainty for Loss-Based Learning M. Pawan Kumar, Benjamin Packer, Daphne Koller

JMLR 2011 Improved Moves for Truncated Convex Models M. Pawan Kumar, Olga Veksler, Philip H.S. Torr

ICCV 2011 Learning Specific-Class Segmentation from Diverse Data M. Pawan Kumar, Haithem Turki, Dan Preston, Daphne Koller

CVPR 2010 Efficiently Selecting Regions for Scene Understanding M. Pawan Kumar, Daphne Koller

CVPR 2010 Energy Minimization for Linear Envelope MRFs Pushmeet Kohli, M. Pawan Kumar

JMLR 2009 An Analysis of Convex Relaxations for MAP Estimation of Discrete MRFs M. Pawan Kumar, Vladimir Kolmogorov, Philip H.S. Torr

ICCV 2009 Efficient Discriminative Learning of Parts-Based Models M. Pawan Kumar, Andrew Zisserman, Philip H. S. Torr

UAI 2009 MAP Estimation of Semi-Metric MRFs via Hierarchical Graph Cuts M. Pawan Kumar, Daphne Koller

ICML 2008 Efficiently Solving Convex Relaxations for MAP Estimation M. Pawan Kumar, Philip H. S. Torr

ICCV 2007 An Invariant Large Margin Nearest Neighbour Classifier M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserman

CVPR 2007 P3 & Beyond: Solving Energies with Higher Order Cliques Pushmeet Kohli, M. Pawan Kumar, Philip H. S. Torr

ECCV 2006 Fast Memory-Efficient Generalized Belief Propagation M. Pawan Kumar, Philip H. S. Torr

CVPR 2006 Solving Markov Random Fields Using Second Order Cone Programming Relaxations M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserman

ICCV 2005 Learning Layered Motion Segmentation of Video M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserman

CVPR 2005 OBJ CUT M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserman