Nakul Verma

According to our database1, Nakul Verma authored at least 30 papers between 2006 and 2023.

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Bibliography

2023
Contrastive Loss is All You Need to Recover Analogies as Parallel Lines.
Proceedings of the 8th Workshop on Representation Learning for NLP, 2023

A Dataset for Learning University STEM Courses at Scale and Generating Questions at a Human Level.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Improving Model Training via Self-learned Label Representations.
CoRR, 2022

Complaint-Driven Training Data Debugging at Interactive Speeds.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

How I stopped worrying about training data bugs and started complaining.
Proceedings of the DEEM '22: Proceedings of the Sixth Workshop on Data Management for End-To-End Machine Learning Philadelphia, 2022

Solving Probability and Statistics Problems by Probabilistic Program Synthesis at Human Level and Predicting Solvability.
Proceedings of the Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners' and Doctoral Consortium, 2022

2021
A Neural Network Solves and Generates Mathematics Problems by Program Synthesis: Calculus, Differential Equations, Linear Algebra, and More.
CoRR, 2021

An analysis of document graph construction methods for AMR summarization.
CoRR, 2021

Solving Probability and Statistics Problems by Program Synthesis.
CoRR, 2021

Solving Linear Algebra by Program Synthesis.
CoRR, 2021

Automated Symbolic Law Discovery: A Computer Vision Approach.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Cortical pattern generation during dexterous movement is input-driven.
Nat., 2020

Biased Programmers? Or Biased Data? A Field Experiment in Operationalizing AI Ethics.
Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

2019
Meta-Learning to Cluster.
CoRR, 2019

Model-Agnostic Meta-Learning using Runge-Kutta Methods.
CoRR, 2019

Metric Learning on Manifolds.
CoRR, 2019

Noise-tolerant fair classification.
CoRR, 2019

2018
Stochastic Neighbor Embedding under f-divergences.
CoRR, 2018

2017
Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality.
J. Mach. Learn. Res., 2017

2015
Sample Complexity of Learning Mahalanobis Distance Metrics.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2013
Efficient energy management and data recovery in sensor networks using latent variables based tensor factorization.
Proceedings of the 16th ACM International Conference on Modeling, 2013

2012
Learning from data with low intrinsic dimension.
PhD thesis, 2012

Distance Preserving Embeddings for General n-Dimensional Manifolds.
Proceedings of the COLT 2012, 2012

CitiSense: improving geospatial environmental assessment of air quality using a wireless personal exposure monitoring system.
Proceedings of the Wireless Health 2012, 2012

Citisense: mobile air quality sensing for individuals and communities.
Proceedings of the SPLASH'12, 2012

Learning hierarchical similarity metrics.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011
Multiple Instance Learning with Manifold Bags.
Proceedings of the 28th International Conference on Machine Learning, 2011

2009
Which Spatial Partition Trees are Adaptive to Intrinsic Dimension?
Proceedings of the UAI 2009, 2009

2007
Learning the structure of manifolds using random projections.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
A Concentration Theorem for Projections.
Proceedings of the UAI '06, 2006


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