Awasthi, Pranjal

64 publications

NeurIPS 2025 From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning Eric Zhao, Pranjal Awasthi, Nika Haghtalab

NeurIPS 2025 Length Generalization via Auxiliary Tasks Pranjal Awasthi, Anupam Gupta, Ravi Kumar

ICML 2025 Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification Eric Zhao, Pranjal Awasthi, Sreenivas Gollapudi

COLT 2024 Learning Neural Networks with Sparse Activations Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka

NeurIPSW 2024 Majority Kernels: An Approach to Leverage Big Model Dynamics for Efficient Small Model Training Hanna Mazzawi, Pranjal Awasthi, Javier Gonzalvo, Srikumar Ramalingam

NeurIPS 2024 Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun

ICMLW 2024 Position Coupling: Leveraging Task Structure for Improved Length Generalization of Transformers Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun

NeurIPS 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

NeurIPS 2024 Semantic Routing via Autoregressive Modeling Eric Zhao, Pranjal Awasthi, Zhengdao Chen, Sreenivas Gollapudi, Daniel Delling

ALT 2024 Semi-Supervised Group DRO: Combating Sparsity with Unlabeled Data Pranjal Awasthi, Satyen Kale, Ankit Pensia

ICLR 2023 Agnostic Learning of General ReLU Activation Using Gradient Descent Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan

COLT 2023 Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes Pranjal Awasthi, Nika Haghtalab, Eric Zhao

AISTATS 2023 Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

AISTATS 2023 Theory and Algorithm for Batch Distribution Drift Problems Pranjal Awasthi, Corinna Cortes, Christopher Mohri

NeurIPSW 2022 A Theory of Learning with Competing Objectives and User Feedback Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri

NeurIPSW 2022 A Theory of Learning with Competing Objectives and User Feedback Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri

ICML 2022 Active Sampling for Min-Max Fairness Jacob D Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Chris Russell, Jie Zhang

ICML 2022 Agnostic Learnability of Halfspaces via Logistic Loss Ziwei Ji, Kwangjun Ahn, Pranjal Awasthi, Satyen Kale, Stefani Karp

AAAI 2022 Beyond GNNs: An Efficient Architecture for Graph Problems Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi

ICML 2022 Congested Bandits: Optimal Routing via Short-Term Resets Pranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias

ICML 2022 Do More Negative Samples Necessarily Hurt in Contrastive Learning? Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath

ICML 2022 H-Consistency Bounds for Surrogate Loss Minimizers Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

ICML 2022 Individual Preference Stability for Clustering Saba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian

NeurIPS 2022 Multi-Class $h$-Consistency Bounds Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2022 On the Adversarial Robustness of Mixture of Experts Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli

ICLR 2022 On the Benefits of Maximum Likelihood Estimation for Regression and Forecasting Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh

NeurIPS 2022 Semi-Supervised Active Linear Regression Nived Rajaraman, Fnu Devvrit, Pranjal Awasthi

NeurIPSW 2022 Theory and Algorithm for Batch Distribution Drift Problems Pranjal Awasthi, Corinna Cortes, Christopher Mohri

NeurIPS 2022 Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen

ALT 2022 Understanding Simultaneous Train and Test Robustness Pranjal Awasthi, Sivaraman Balakrishnan, Aravindan Vijayaraghavan

NeurIPS 2021 A Convergence Analysis of Gradient Descent on Graph Neural Networks Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi

ALT 2021 A Deep Conditioning Treatment of Neural Networks Naman Agarwal, Pranjal Awasthi, Satyen Kale

CVPR 2021 Adversarial Robustness Across Representation Spaces Pranjal Awasthi, George Yu, Chun-Sung Ferng, Andrew Tomkins, Da-Cheng Juan

COLT 2021 Adversarially Robust Low Dimensional Representations Pranjal Awasthi, Vaggos Chatziafratis, Xue Chen, Aravindan Vijayaraghavan

NeurIPS 2021 Calibration and Consistency of Adversarial Surrogate Losses Pranjal Awasthi, Natalie Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2021 Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan

NeurIPS 2021 Neural Active Learning with Performance Guarantees Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile

NeurIPS 2021 On the Existence of the Adversarial Bayes Classifier Pranjal Awasthi, Natalie Frank, Mehryar Mohri

ICML 2020 Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks Pranjal Awasthi, Natalie Frank, Mehryar Mohri

NeurIPS 2020 Adversarial Robustness via Robust Low Rank Representations Pranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan

NeurIPS 2020 Efficient Active Learning of Sparse Halfspaces with Arbitrary Bounded Noise Chicheng Zhang, Jie Shen, Pranjal Awasthi

AISTATS 2020 Equalized Odds Postprocessing Under Imperfect Group Information Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern

COLT 2020 Estimating Principal Components Under Adversarial Perturbations Pranjal Awasthi, Xue Chen, Aravindan Vijayaraghavan

NeurIPS 2020 PAC-Bayes Learning Bounds for Sample-Dependent Priors Pranjal Awasthi, Satyen Kale, Stefani Karp, Mehryar Mohri

ICML 2019 Fair K-Center Clustering for Data Summarization Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern

ICML 2019 Guarantees for Spectral Clustering with Fairness Constraints Matthäus Kleindessner, Samira Samadi, Pranjal Awasthi, Jamie Morgenstern

NeurIPS 2019 On Robustness to Adversarial Examples and Polynomial Optimization Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan

AISTATS 2019 Robust Matrix Completion from Quantized Observations Jie Shen, Pranjal Awasthi, Ping Li

ICML 2018 Clustering Semi-Random Mixtures of Gaussians Aravindan Vijayaraghavan, Pranjal Awasthi

ICML 2018 Crowdsourcing with Arbitrary Adversaries Matthaeus Kleindessner, Pranjal Awasthi

AISTATS 2018 Robust Vertex Enumeration for Convex Hulls in High Dimensions Pranjal Awasthi, Bahman Kalantari, Yikai Zhang

COLT 2017 Efficient PAC Learning from the Crowd Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour

JMLR 2017 Local Algorithms for Interactive Clustering Pranjal Awasthi, Maria Florina Balcan, Konstantin Voevodski

COLT 2016 Learning and 1-Bit Compressed Sensing Under Asymmetric Noise Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Hongyang Zhang

COLT 2015 Efficient Learning of Linear Separators Under Bounded Noise Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner

COLT 2015 Label Optimal Regret Bounds for Online Local Learning Pranjal Awasthi, Moses Charikar, Kevin A. Lai, Andrej Risteski

NeurIPS 2015 On Some Provably Correct Cases of Variational Inference for Topic Models Pranjal Awasthi, Andrej Risteski

NeurIPS 2014 Learning Mixtures of Ranking Models Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan

ICML 2014 Local Algorithms for Interactive Clustering Pranjal Awasthi, Maria Balcan, Konstantin Voevodski

COLT 2013 Learning Using Local Membership Queries Pranjal Awasthi, Vitaly Feldman, Varun Kanade

COLT 2010 Improved Guarantees for Agnostic Learning of Disjunctions Pranjal Awasthi, Avrim Blum, Or Sheffet

NeurIPS 2010 Supervised Clustering Pranjal Awasthi, Reza B. Zadeh

IJCAI 2009 Online Stochastic Optimization in the Large: Application to Kidney Exchange Pranjal Awasthi, Tuomas Sandholm

IJCAI 2007 Image Modeling Using Tree Structured Conditional Random Fields Pranjal Awasthi, Aakanksha Gagrani, Balaraman Ravindran