Nakul Verma - RankMe

42 papers A* 6A 3Journal 24Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Compressibility Barriers to Neighborhood-Preserving Data Visualizations. CoRR Szymon Snoeck, Noah Bergam, Nakul Verma
2025	J	`jnl`	Deep Autoregressive Models as Causal Inference Engines. Trans. Mach. Learn. Res. Daniel Jiwoong Im, Kevin Zhang, Nakul Verma, Kyunghyun Cho
2025	J	`jnl`	Diverse Inference and Verification for Advanced Reasoning. CoRR Iddo Drori, Gaston Longhitano, Mao Mao, Seunghwan Hyun, Yuke Zhang, Sungjun Park, Zachary Meeks, Xin-Yu Zhang, Ben Segev, Howard Yong, Nakul Verma, Avi Shporer, Alon Amit, Madeleine Udell
2025	J	`jnl`	LogicLearner: A Tool for the Guided Practice of Propositional Logic Proofs. CoRR Amogh Inamdar, Uzay Macar, Michel Vazirani, Michael Tarnow, Zarina Mustapha, Natalia Dittren, Sam Sadeh, Nakul Verma, Ansaf Salleb-Aouissi
2025	J	`jnl`	t-SNE Exaggerates Clusters, Provably. CoRR Noah Bergam, Szymon Snoeck, Nakul Verma
2024	J	`jnl`	Using Deep Autoregressive Models as Causal Inference Engines. CoRR Daniel Jiwoong Im, Kevin Zhang, Nakul Verma, Kyunghyun Cho
2023	A*	`conf`	A Dataset for Learning University STEM Courses at Scale and Generating Questions at a Human Level. AAAI 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
2023	—	`conf`	Contrastive Loss is All You Need to Recover Analogies as Parallel Lines. RepL4NLP@ACL Narutatsu Ri, Fei-Tzin Lee, Nakul Verma
2023	J	`jnl`	Contrastive Loss is All You Need to Recover Analogies as Parallel Lines. CoRR Narutatsu Ri, Fei-Tzin Lee, Nakul Verma
2022	—	`conf`	Complaint-Driven Training Data Debugging at Interactive Speeds. SIGMOD Conference Lampros Flokas, Weiyuan Wu, Yejia Liu, Jiannan Wang, Nakul Verma, Eugene Wu
2022	—	`conf`	How I stopped worrying about training data bugs and started complaining. DEEM@SIGMOD Lampros Flokas, Weiyuan Wu, Jiannan Wang, Nakul Verma, Eugene Wu
2022	J	`jnl`	Improving Model Training via Self-learned Label Representations. CoRR Xiao Yu, Nakul Verma
2022	—	`conf`	Solving Probability and Statistics Problems by Probabilistic Program Synthesis at Human Level and Predicting Solvability. AIED (2) Leonard Tang, Elizabeth Ke, Nikhil Singh, Bo Feng, Derek Austin, Nakul Verma, Iddo Drori
2021	J	`jnl`	A Neural Network Solves and Generates Mathematics Problems by Program Synthesis: Calculus, Differential Equations, Linear Algebra, and More. CoRR Iddo Drori, Sunny Tran, Roman Wang, Newman Cheng, Kevin Liu, Leonard Tang, Elizabeth Ke, Nikhil Singh, Taylor L. Patti, Jayson Lynch, Avi Shporer, Nakul Verma, Eugene Wu, Gilbert Strang
2021	J	`jnl`	An analysis of document graph construction methods for AMR summarization. CoRR Fei-Tzin Lee, Chris Kedzie, Nakul Verma, Kathleen R. McKeown
2021	A*	`conf`	Automated Symbolic Law Discovery: A Computer Vision Approach. AAAI Hengrui Xing, Ansaf Salleb-Aouissi, Nakul Verma
2021	J	`jnl`	Solving Linear Algebra by Program Synthesis. CoRR Iddo Drori, Nakul Verma
2021	J	`jnl`	Solving Probability and Statistics Problems by Program Synthesis. CoRR Leonard Tang, Elizabeth Ke, Nikhil Singh, Nakul Verma, Iddo Drori
2020	A*	`conf`	Biased Programmers? Or Biased Data? A Field Experiment in Operationalizing AI Ethics. EC Bo Cowgill, Fabrizio Dell'Acqua, Samuel Deng, Daniel Hsu, Nakul Verma, Augustin Chaintreau
2020	J	`jnl`	Biased Programmers? Or Biased Data? A Field Experiment in Operationalizing AI Ethics. CoRR Bo Cowgill, Fabrizio Dell'Acqua, Samuel Deng, Daniel Hsu, Nakul Verma, Augustin Chaintreau
2020	J	`jnl`	Cortical pattern generation during dexterous movement is input-driven. Nat. Britton A. Sauerbrei, Jian-Zhong Guo, Jeremy D. Cohen, Matteo Mischiati, Wendy Guo, Mayank Kabra, Nakul Verma, Brett Mensh, Kristin Branson, Adam W. Hantman
2019	J	`jnl`	Meta-Learning to Cluster. CoRR Yibo Jiang, Nakul Verma
2019	J	`jnl`	Metric Learning on Manifolds. CoRR Max Aalto, Nakul Verma
2019	J	`jnl`	Model-Agnostic Meta-Learning using Runge-Kutta Methods. CoRR Daniel Jiwoong Im, Yibo Jiang, Nakul Verma
2019	J	`jnl`	Noise-tolerant fair classification. CoRR Alexandre Louis Lamy, Ziyuan Zhong, Aditya Krishna Menon, Nakul Verma
2018	J	`jnl`	Stochastic Neighbor Embedding under f-divergences. CoRR Daniel Jiwoong Im, Nakul Verma, Kristin Branson
2017	J	`jnl`	Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality. J. Mach. Learn. Res. Samory Kpotufe, Nakul Verma
2015	—	`conf`	Sample Complexity of Learning Mahalanobis Distance Metrics. NIPS Nakul Verma, Kristin Branson
2015	J	`jnl`	Sample complexity of learning Mahalanobis distance metrics. CoRR Nakul Verma, Kristin Branson
2013	J	`jnl`	Distance preserving embeddings for general n-dimensional manifolds. J. Mach. Learn. Res. Nakul Verma
2013	A	`conf`	Efficient energy management and data recovery in sensor networks using latent variables based tensor factorization. MSWiM Bojan Milosevic, Jinseok Yang, Nakul Verma, Sameer S. Tilak, Piero Zappi, Elisabetta Farella, Luca Benini, Tajana Simunic Rosing
2012	J	`jnl`	A concentration theorem for projections. CoRR Sanjoy Dasgupta, Daniel J. Hsu, Nakul Verma
2012	—	`conf`	CitiSense: improving geospatial environmental assessment of air quality using a wireless personal exposure monitoring system. Wireless Health Nima Nikzad, Nakul Verma, Celal Ziftci, Elizabeth S. Bales, Nichole Quick, Piero Zappi, Kevin Patrick, Sanjoy Dasgupta, Ingolf Krueger, Tajana Simunic Rosing, William G. Griswold
2012	—	`conf`	Citisense: mobile air quality sensing for individuals and communities. SPLASH Celal Ziftci, Nima Nikzad, Nakul Verma, Piero Zappi, Elizabeth S. Bales, Ingolf Krueger, William G. Griswold
2012	A*	`conf`	Distance Preserving Embeddings for General n-Dimensional Manifolds. COLT Nakul Verma
2012	—	`—`	Learning from data with low intrinsic dimension. Nakul Verma
2012	A*	`conf`	Learning hierarchical similarity metrics. CVPR Nakul Verma, Dhruv Mahajan, Sundararajan Sellamanickam, Vinod Nair
2012	J	`jnl`	Which Spatial Partition Trees are Adaptive to Intrinsic Dimension? CoRR Nakul Verma, Samory Kpotufe, Sanjoy Dasgupta
2011	A*	`conf`	Multiple Instance Learning with Manifold Bags. ICML Boris Babenko, Nakul Verma, Piotr Dollár, Serge J. Belongie
2009	A	`conf`	Which Spatial Partition Trees are Adaptive to Intrinsic Dimension? UAI Nakul Verma, Samory Kpotufe, Sanjoy Dasgupta
2007	—	`conf`	Learning the structure of manifolds using random projections. NIPS Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul Verma
2006	A	`conf`	A Concentration Theorem for Projections. UAI Sanjoy Dasgupta, Daniel J. Hsu, Nakul Verma