Verma, Nakul

13 publications

TMLR 2025 Deep Autoregressive Models as Causal Inference Engines Daniel Jiwoong Im, Kevin Zhang, Nakul Verma, Kyunghyun Cho

AAAI 2023 A Dataset for Learning University STEM Courses at Scale and Generating Questions at a Human Level Iddo Drori, Sarah J. Zhang, Zad Chin, Reece Shuttleworth, Albert Lu, Linda Chen, Bereket Birbo, Michele He, Pedro Lantigua, Sunny Tran, Gregory Hunter, Bo Feng, Newman Cheng, Roman Wang, Yann Hicke, Saisamrit Surbehera, Arvind Raghavan, Alexander E. Siemenn, Nikhil Singh, Jayson Lynch, Avi Shporer, Nakul Verma, Tonio Buonassisi, Armando Solar-Lezama

AAAI 2021 Automated Symbolic Law Discovery: A Computer Vision Approach Hengrui Xing, Ansaf Salleb-Aouissi, Nakul Verma

NeurIPS 2019 Noise-Tolerant Fair Classification Alex Lamy, Ziyuan Zhong, Aditya K Menon, Nakul Verma

JMLR 2017 Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality Samory Kpotufe, Nakul Verma

NeurIPS 2015 Sample Complexity of Learning Mahalanobis Distance Metrics Nakul Verma, Kristin Branson

JMLR 2013 Distance Preserving Embeddings for General N-Dimensional Manifolds Nakul Verma

COLT 2012 Distance Preserving Embeddings for General N-Dimensional Manifolds Nakul Verma

CVPR 2012 Learning Hierarchical Similarity Metrics Nakul Verma, Dhruv Mahajan, Sundararajan Sellamanickam, Vinod Nair

ICML 2011 Multiple Instance Learning with Manifold Bags Boris Babenko, Nakul Verma, Piotr Dollár, Serge J. Belongie

UAI 2009 Which Spatial Partition Trees Are Adaptive to Intrinsic Dimension? Nakul Verma, Samory Kpotufe, Sanjoy Dasgupta

NeurIPS 2007 Learning the Structure of Manifolds Using Random Projections Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul Verma

UAI 2006 A Concentration Theorem for Projections Sanjoy Dasgupta, Daniel J. Hsu, Nakul Verma