Pranjal Awasthi

According to our database, Pranjal Awasthi authored at least 102 papers between 2007 and 2024.

Collaborative distances:

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2024

Best-effort adaptation.

Pranjal Awasthi, Corinna Cortes, Mehryar Mohri

Ann. Math. Artif. Intell., April, 2024

ReMI: A Dataset for Reasoning with Multiple Images.

Mehran Kazemi, Nishanth Dikkala, Ankit Anand, Petar Devic, Ishita Dasgupta, Fangyu Liu, Bahare Fatemi, Pranjal Awasthi, Dee Guo, Sreenivas Gollapudi, Ahmed Qureshi

CoRR, 2024

Long-Span Question-Answering: Automatic Question Generation and QA-System Ranking via Side-by-Side Evaluation.

Bernd Bohnet, Kevin Swersky, Rosanne Liu, Pranjal Awasthi, Azade Nova, Javier Snaider, Hanie Sedghi, Aaron T. Parisi, Michael Collins, Angeliki Lazaridou, Orhan Firat, Noah Fiedel

CoRR, 2024

Position Coupling: Leveraging Task Structure for Improved Length Generalization of Transformers.

Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun

CoRR, 2024

Stacking as Accelerated Gradient Descent.

Naman Agarwal, Pranjal Awasthi, Satyen Kale, Eric Zhao

CoRR, 2024

On Distributed Larger-Than-Memory Subset Selection With Pairwise Submodular Functions.

Maximilian Böther, Abraham Sebastian, Pranjal Awasthi, Ana Klimovic, Srikumar Ramalingam

CoRR, 2024

Simulated Overparameterization.

Hanna Mazzawi, Pranjal Awasthi, Xavi Gonzalvo, Srikumar Ramalingam

CoRR, 2024

A Theory of Learning with Competing Objectives and User Feedback.

Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri

Proceedings of the Artificial Intelligence and Image Analysis, 2024

Learning Neural Networks with Sparse Activations.

Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Semi-supervised Group DRO: Combating Sparsity with Unlabeled Data.

Pranjal Awasthi, Satyen Kale, Ankit Pensia

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

2023

Does Engaging in Data Philanthropy Impact Business Value?

Jordana J. George, Jie (Kevin) Yan, Dorothy E. Leidner, Pranjal Awasthi

Inf. Syst. Manag., April, 2023

A Weighted K-Center Algorithm for Data Subset Selection.

Srikumar Ramalingam, Pranjal Awasthi, Sanjiv Kumar

CoRR, 2023

Improving Length-Generalization in Transformers via Task Hinting.

Pranjal Awasthi, Anupam Gupta

CoRR, 2023

The Sample Complexity of Multi-Distribution Learning for VC Classes.

Pranjal Awasthi, Nika Haghtalab, Eric Zhao

CoRR, 2023

Agnostic Learning of General ReLU Activation Using Gradient Descent.

Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Distributionally Robust Data Join.

Pranjal Awasthi, Christopher Jung, Jamie Morgenstern

Proceedings of the 4th Symposium on Foundations of Responsible Computing, 2023

Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes.

Pranjal Awasthi, Nika Haghtalab, Eric Zhao

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness.

Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Theory and Algorithm for Batch Distribution Drift Problems.

Pranjal Awasthi, Corinna Cortes, Christopher Mohri

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models.

Weihao Kong, Rajat Sen, Pranjal Awasthi, Abhimanyu Das

CoRR, 2022

H-Consistency Estimation Error of Surrogate Loss Minimizers.

Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

CoRR, 2022

Semi-supervised Active Linear Regression.

Nived Rajaraman, Devvrit, Pranjal Awasthi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Adversarial Robustness of Mixture of Experts.

Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-Class $H$-Consistency Bounds.

Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model.

Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Agnostic Learnability of Halfspaces via Logistic Loss.

Ziwei Ji, Kwangjun Ahn, Pranjal Awasthi, Satyen Kale, Stefani Karp

Proceedings of the International Conference on Machine Learning, 2022

H-Consistency Bounds for Surrogate Loss Minimizers.

Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

Proceedings of the International Conference on Machine Learning, 2022

Do More Negative Samples Necessarily Hurt In Contrastive Learning?

Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath

Proceedings of the International Conference on Machine Learning, 2022

Congested Bandits: Optimal Routing via Short-term Resets.

Pranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias

Proceedings of the International Conference on Machine Learning, 2022

Individual Preference Stability for Clustering.

Saba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian

Proceedings of the International Conference on Machine Learning, 2022

Active Sampling for Min-Max Fairness.

Jacob D. Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Chris Russell, Jie Zhang

Proceedings of the International Conference on Machine Learning, 2022

On the benefits of maximum likelihood estimation for Regression and Forecasting.

Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh

Proceedings of the Tenth International Conference on Learning Representations, 2022

Effective and Inconspicuous Over-the-Air Adversarial Examples with Adaptive Filtering.

Patrick O'Reilly, Pranjal Awasthi, Aravindan Vijayaraghavan, Bryan Pardo

Proceedings of the IEEE International Conference on Acoustics, 2022

Understanding Simultaneous Train and Test Robustness.

Pranjal Awasthi, Sivaraman Balakrishnan, Aravindan Vijayaraghavan

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Beyond GNNs: An Efficient Architecture for Graph Problems.

Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

On the Existence of the Adversarial Bayes Classifier (Extended Version).

Pranjal Awasthi, Natalie S. Frank, Mehryar Mohri

CoRR, 2021

Semi-supervised Active Regression.

Devvrit, Nived Rajaraman, Pranjal Awasthi

CoRR, 2021

A Finer Calibration Analysis for Adversarial Robustness.

Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

CoRR, 2021

A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness.

Jacob D. Abernethy, Pranjal Awasthi, Satyen Kale

CoRR, 2021

Neural Active Learning with Performance Guarantees.

Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations.

Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Calibration and Consistency of Adversarial Surrogate Losses.

Pranjal Awasthi, Natalie Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Existence of The Adversarial Bayes Classifier.

Pranjal Awasthi, Natalie Frank, Mehryar Mohri

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Convergence Analysis of Gradient Descent on Graph Neural Networks.

Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information.

Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Adversarial Robustness Across Representation Spaces.

Pranjal Awasthi, George Yu, Chun-Sung Ferng, Andrew Tomkins, Da-Cheng Juan

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Adversarially Robust Low Dimensional Representations.

Pranjal Awasthi, Vaggos Chatziafratis, Xue Chen, Aravindan Vijayaraghavan

Proceedings of the Conference on Learning Theory, 2021

A Deep Conditioning Treatment of Neural Networks.

Naman Agarwal, Pranjal Awasthi, Satyen Kale

Proceedings of the Algorithmic Learning Theory, 2021

Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective.

Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

Beyond Individual and Group Fairness.

Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri

CoRR, 2020

On the Rademacher Complexity of Linear Hypothesis Sets.

Pranjal Awasthi, Natalie Frank, Mehryar Mohri

CoRR, 2020

Adaptive Sampling to Reduce Disparate Performance.

Jacob D. Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Jie Zhang

CoRR, 2020

A Notion of Individual Fairness for Clustering.

Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern

CoRR, 2020

Robust vertex enumeration for convex hulls in high dimensions.

Pranjal Awasthi, Bahman Kalantari, Yikai Zhang

Ann. Oper. Res., 2020

Efficient active learning of sparse halfspaces with arbitrary bounded noise.

Chicheng Zhang, Jie Shen, Pranjal Awasthi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

PAC-Bayes Learning Bounds for Sample-Dependent Priors.

Pranjal Awasthi, Satyen Kale, Stefani Karp, Mehryar Mohri

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adversarial robustness via robust low rank representations.

Pranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks.

Pranjal Awasthi, Natalie Frank, Mehryar Mohri

Proceedings of the 37th International Conference on Machine Learning, 2020

The Impact of Data Philanthropy on Global Health When Mediated Through Digital Epidemiology.

Pranjal Awasthi, Jordana J. George

Proceedings of the 41st International Conference on Information Systems, 2020

Estimating Principal Components under Adversarial Perturbations.

Pranjal Awasthi, Xue Chen, Aravindan Vijayaraghavan

Proceedings of the Conference on Learning Theory, 2020

A case for Data Democratization.

Pranjal Awasthi, Jordana J. George

Proceedings of the 26th Americas Conference on Information Systems, 2020

Equalized odds postprocessing under imperfect group information.

Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

On the adaptivity gap in two-stage robust linear optimization under uncertain packing constraints.

Pranjal Awasthi, Vineet Goyal, Brian Y. Lu

Math. Program., 2019

Effectiveness of Equalized Odds for Fair Classification under Imperfect Group Information.

Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern

CoRR, 2019

On Robustness to Adversarial Examples and Polynomial Optimization.

Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Guarantees for Spectral Clustering with Fairness Constraints.

Matthäus Kleindessner, Samira Samadi, Pranjal Awasthi, Jamie Morgenstern

Proceedings of the 36th International Conference on Machine Learning, 2019

Fair k-Center Clustering for Data Summarization.

Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern

Proceedings of the 36th International Conference on Machine Learning, 2019

Robust Communication-Optimal Distributed Clustering Algorithms.

Pranjal Awasthi, Ainesh Bakshi, Maria-Florina Balcan, Colin White, David P. Woodruff

Proceedings of the 46th International Colloquium on Automata, Languages, and Programming, 2019

Bilu-Linial Stability, Certified Algorithms and the Independent Set Problem.

Haris Angelidakis, Pranjal Awasthi, Avrim Blum, Vaggos Chatziafratis, Chen Dan

Proceedings of the 27th Annual European Symposium on Algorithms, 2019

Robust Matrix Completion from Quantized Observations.

Jie Shen, Pranjal Awasthi, Ping Li

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Crowdsourcing with Arbitrary Adversaries.

Matthäus Kleindessner, Pranjal Awasthi

Proceedings of the 35th International Conference on Machine Learning, 2018

Clustering Semi-Random Mixtures of Gaussians.

Pranjal Awasthi, Aravindan Vijayaraghavan

Proceedings of the 35th International Conference on Machine Learning, 2018

Towards Learning Sparsely Used Dictionaries with Arbitrary Supports.

Pranjal Awasthi, Aravindan Vijayaraghavan

Proceedings of the 59th IEEE Annual Symposium on Foundations of Computer Science, 2018

2017

Local algorithms for interactive clustering.

Pranjal Awasthi, Maria-Florina Balcan, Konstantin Voevodski

J. Mach. Learn. Res., 2017

The Power of Localization for Efficiently Learning Linear Separators with Noise.

Pranjal Awasthi, Maria-Florina Balcan, Philip M. Long

J. ACM, 2017

General and Robust Communication-Efficient Algorithms for Distributed Clustering.

Pranjal Awasthi, Maria-Florina Balcan, Colin White

CoRR, 2017

Efficient PAC Learning from the Crowd.

Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour

Proceedings of the 30th Conference on Learning Theory, 2017

2016

Clustering Under Stability Assumptions.

Pranjal Awasthi

Encyclopedia of Algorithms, 2016

Spectral Embedding of k-Cliques, Graph Partitioning and k-Means.

Pranjal Awasthi, Moses Charikar, Ravishankar Krishnaswamy, Ali Kemal Sinop

Proceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science, 2016

Learning and 1-bit Compressed Sensing under Asymmetric Noise.

Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Hongyang Zhang

Proceedings of the 29th Conference on Learning Theory, 2016

2015

On some provably correct cases of variational inference for topic models.

Pranjal Awasthi, Andrej Risteski

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Relax, No Need to Round: Integrality of Clustering Formulations.

Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel A. Ward

Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science, 2015

The Hardness of Approximation of Euclidean k-Means.

Pranjal Awasthi, Moses Charikar, Ravishankar Krishnaswamy, Ali Kemal Sinop

Proceedings of the 31st International Symposium on Computational Geometry, 2015

Label optimal regret bounds for online local learning.

Pranjal Awasthi, Moses Charikar, Kevin A. Lai, Andrej Risteski

Proceedings of The 28th Conference on Learning Theory, 2015

Efficient Learning of Linear Separators under Bounded Noise.

Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner

Proceedings of The 28th Conference on Learning Theory, 2015

2014

Learning Mixtures of Ranking Models.

Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Approximation Algorithms and New Models for Clustering and Learning.

Pranjal Awasthi

PhD thesis, 2013

The Power of Localization for Efficiently Learning Linear Separators with Malicious Noise.

Pranjal Awasthi, Maria-Florina Balcan, Philip M. Long

CoRR, 2013

Learning Using Local Membership Queries.

Pranjal Awasthi, Vitaly Feldman, Varun Kanade

Proceedings of the COLT 2013, 2013

2012

Center-based clustering under perturbation stability.

Pranjal Awasthi, Avrim Blum, Or Sheffet

Inf. Process. Lett., 2012

Testing Lipschitz Functions on Hypergrid Domains.

Pranjal Awasthi, Madhav Jha, Marco Molinaro, Sofya Raskhodnikova

Electron. Colloquium Comput. Complex., 2012

Limitations of Local Filters of Lipschitz and Monotone Functions.

Pranjal Awasthi, Madhav Jha, Marco Molinaro, Sofya Raskhodnikova

Electron. Colloquium Comput. Complex., 2012

Learning using Local Membership Queries under Smooth Distributions

Pranjal Awasthi, Varun Kanade

CoRR, 2012

Improved Spectral-Norm Bounds for Clustering.

Pranjal Awasthi, Or Sheffet

Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 2012

Additive Approximation for Near-Perfect Phylogeny Construction.

Pranjal Awasthi, Avrim Blum, Jamie Morgenstern, Or Sheffet

Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 2012

2011

Decision trees for entity identification: Approximation algorithms and hardness results.

Venkatesan T. Chakaravarthy, Vinayaka Pandit, Sambuddha Roy, Pranjal Awasthi, Mukesh K. Mohania

ACM Trans. Algorithms, 2011

2010

On Nash-Equilibria of Approximation-Stable Games.

Pranjal Awasthi, Maria-Florina Balcan, Avrim Blum, Or Sheffet, Santosh S. Vempala

Proceedings of the Algorithmic Game Theory - Third International Symposium, 2010

Supervised Clustering.

Pranjal Awasthi, Reza Bosagh Zadeh

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Stability Yields a PTAS for k-Median and k-Means Clustering.

Pranjal Awasthi, Avrim Blum, Or Sheffet

Proceedings of the 51th Annual IEEE Symposium on Foundations of Computer Science, 2010

Improved Guarantees for Agnostic Learning of Disjunctions.

Pranjal Awasthi, Avrim Blum, Or Sheffet

Proceedings of the COLT 2010, 2010

2009

Online Stochastic Optimization in the Large: Application to Kidney Exchange.

Pranjal Awasthi, Tuomas Sandholm

Proceedings of the IJCAI 2009, 2009

2007

Image Modeling Using Tree Structured Conditional Random Fields.

Pranjal Awasthi, Aakanksha Gagrani, Balaraman Ravindran

Proceedings of the IJCAI 2007, 2007