Pranjal Awasthi

160 papers A* 51A 8B 4C 2Misc 2Journal 80Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Combinatorial Optimization via LLM-driven Iterated Fine-tuning. CoRR Pranjal Awasthi, Sreenivas Gollapudi, Ravi Kumar, Kamesh Munagala
2025	J	`jnl`	Enhancing LLM Planning Capabilities through Intrinsic Self-Critique. CoRR Bernd Bohnet, Pierre-Alexandre Kamienny, Hanie Sedghi, Dilan Görür, Pranjal Awasthi, Aaron Parisi, Kevin Swersky, Rosanne Liu, Azade Nova, Noah Fiedel
2025	J	`jnl`	From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning. CoRR Eric Zhao, Pranjal Awasthi, Nika Haghtalab
2025	—	`conf`	On Distributed Larger-Than-Memory Subset Selection With Pairwise Submodular Functions. MLSys Maximilian Böther, Abraham Sebastian, Pranjal Awasthi, Ana Klimovic, Srikumar Ramalingam
2025	A*	`conf`	Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification. ICML Eric Zhao, Pranjal Awasthi, Sreenivas Gollapudi
2025	J	`jnl`	Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification. CoRR Eric Zhao, Pranjal Awasthi, Sreenivas Gollapudi
2025	J	`jnl`	The Limits of Preference Data for Post-Training. CoRR Eric Zhao, Jessica Dai, Pranjal Awasthi
2024	Misc	`conf`	A Theory of Learning with Competing Objectives and User Feedback. ISAIM Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri
2024	J	`jnl`	Best-effort adaptation. Ann. Math. Artif. Intell. Pranjal Awasthi, Corinna Cortes, Mehryar Mohri
2024	A*	`conf`	Learning Neural Networks with Sparse Activations. COLT Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka
2024	J	`jnl`	Learning Neural Networks with Sparse Activations. CoRR Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka
2024	J	`jnl`	Long-Span Question-Answering: Automatic Question Generation and QA-System Ranking via Side-by-Side Evaluation. CoRR 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
2024	J	`jnl`	On Distributed Larger-Than-Memory Subset Selection With Pairwise Submodular Functions. CoRR Maximilian Böther, Abraham Sebastian, Pranjal Awasthi, Ana Klimovic, Srikumar Ramalingam
2024	A*	`conf`	Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure. NeurIPS Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun
2024	J	`jnl`	Position Coupling: Leveraging Task Structure for Improved Length Generalization of Transformers. CoRR Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun
2024	A*	`conf`	ReMI: A Dataset for Reasoning with Multiple Images. NeurIPS Mehran Kazemi, Nishanth Dikkala, Ankit Anand, Petar Devic, Ishita Dasgupta, Fangyu Liu, Bahare Fatemi, Pranjal Awasthi, Sreenivas Gollapudi, Dee Guo, Ahmed Qureshi
2024	J	`jnl`	ReMI: A Dataset for Reasoning with Multiple Images. CoRR Mehran Kazemi, Nishanth Dikkala, Ankit Anand, Petar Devic, Ishita Dasgupta, Fangyu Liu, Bahare Fatemi, Pranjal Awasthi, Dee Guo, Sreenivas Gollapudi, Ahmed Qureshi
2024	A*	`conf`	Semantic Routing via Autoregressive Modeling. NeurIPS Eric Zhao, Pranjal Awasthi, Zhengdao Chen, Sreenivas Gollapudi, Daniel Delling
2024	B	`conf`	Semi-supervised Group DRO: Combating Sparsity with Unlabeled Data. ALT Pranjal Awasthi, Satyen Kale, Ankit Pensia
2024	J	`jnl`	Simulated Overparameterization. CoRR Hanna Mazzawi, Pranjal Awasthi, Xavi Gonzalvo, Srikumar Ramalingam
2024	J	`jnl`	Stacking as Accelerated Gradient Descent. CoRR Naman Agarwal, Pranjal Awasthi, Satyen Kale, Eric Zhao
2023	J	`jnl`	A Weighted K-Center Algorithm for Data Subset Selection. CoRR Srikumar Ramalingam, Pranjal Awasthi, Sanjiv Kumar
2023	A*	`conf`	Agnostic Learning of General ReLU Activation Using Gradient Descent. ICLR Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan
2023	J	`jnl`	Best-Effort Adaptation. CoRR Pranjal Awasthi, Corinna Cortes, Mehryar Mohri
2023	J	`jnl`	Congested Bandits: Optimal Routing via Short-term Resets. CoRR Pranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias
2023	—	`conf`	Distributionally Robust Data Join. FORC Pranjal Awasthi, Christopher Jung, Jamie Morgenstern
2023	J	`jnl`	Does Engaging in Data Philanthropy Impact Business Value? Inf. Syst. Manag. Jordana J. George, Jie (Kevin) Yan, Dorothy E. Leidner, Pranjal Awasthi
2023	J	`jnl`	Improving Length-Generalization in Transformers via Task Hinting. CoRR Pranjal Awasthi, Anupam Gupta
2023	A*	`conf`	Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes. COLT Pranjal Awasthi, Nika Haghtalab, Eric Zhao
2023	J	`jnl`	The Sample Complexity of Multi-Distribution Learning for VC Classes. CoRR Pranjal Awasthi, Nika Haghtalab, Eric Zhao
2023	A	`conf`	Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness. AISTATS Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong
2023	A	`conf`	Theory and Algorithm for Batch Distribution Drift Problems. AISTATS Pranjal Awasthi, Corinna Cortes, Christopher Mohri
2022	A*	`conf`	Active Sampling for Min-Max Fairness. ICML Jacob D. Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Chris Russell, Jie Zhang
2022	A*	`conf`	Agnostic Learnability of Halfspaces via Logistic Loss. ICML Ziwei Ji, Kwangjun Ahn, Pranjal Awasthi, Satyen Kale, Stefani Karp
2022	J	`jnl`	Agnostic Learnability of Halfspaces via Logistic Loss. CoRR Ziwei Ji, Kwangjun Ahn, Pranjal Awasthi, Satyen Kale, Stefani Karp
2022	J	`jnl`	Agnostic Learning of General ReLU Activation Using Gradient Descent. CoRR Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan
2022	A*	`conf`	Beyond GNNs: An Efficient Architecture for Graph Problems. AAAI Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi
2022	A*	`conf`	Congested Bandits: Optimal Routing via Short-term Resets. ICML Pranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias
2022	J	`jnl`	Distributionally Robust Data Join. CoRR Pranjal Awasthi, Christopher Jung, Jamie Morgenstern
2022	A*	`conf`	Do More Negative Samples Necessarily Hurt In Contrastive Learning? ICML Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath
2022	J	`jnl`	Do More Negative Samples Necessarily Hurt in Contrastive Learning? CoRR Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath
2022	Misc	`conf`	Effective and Inconspicuous Over-the-Air Adversarial Examples with Adaptive Filtering. ICASSP Patrick O'Reilly, Pranjal Awasthi, Aravindan Vijayaraghavan, Bryan Pardo
2022	A*	`conf`	H-Consistency Bounds for Surrogate Loss Minimizers. ICML Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong
2022	J	`jnl`	H-Consistency Estimation Error of Surrogate Loss Minimizers. CoRR Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong
2022	A*	`conf`	Individual Preference Stability for Clustering. ICML Saba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian
2022	J	`jnl`	Individual Preference Stability for Clustering. CoRR Saba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian
2022	A*	`conf`	Multi-Class $H$-Consistency Bounds. NeurIPS Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong
2022	A*	`conf`	On the Adversarial Robustness of Mixture of Experts. NeurIPS Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli
2022	J	`jnl`	On the Adversarial Robustness of Mixture of Experts. CoRR Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli
2022	A*	`conf`	On the benefits of maximum likelihood estimation for Regression and Forecasting. ICLR Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh
2022	A*	`conf`	Semi-supervised Active Linear Regression. NeurIPS Nived Rajaraman, Devvrit, Pranjal Awasthi
2022	A*	`conf`	Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model. NeurIPS Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen
2022	J	`jnl`	Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models. CoRR Weihao Kong, Rajat Sen, Pranjal Awasthi, Abhimanyu Das
2022	B	`conf`	Understanding Simultaneous Train and Test Robustness. ALT Pranjal Awasthi, Sivaraman Balakrishnan, Aravindan Vijayaraghavan
2021	A*	`conf`	A Convergence Analysis of Gradient Descent on Graph Neural Networks. NeurIPS Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi
2021	B	`conf`	A Deep Conditioning Treatment of Neural Networks. ALT Naman Agarwal, Pranjal Awasthi, Satyen Kale
2021	J	`jnl`	A Finer Calibration Analysis for Adversarial Robustness. CoRR Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong
2021	J	`jnl`	A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness. CoRR Jacob D. Abernethy, Pranjal Awasthi, Satyen Kale
2021	A*	`conf`	Adversarial Robustness Across Representation Spaces. CVPR Pranjal Awasthi, George Yu, Chun-Sung Ferng, Andrew Tomkins, Da-Cheng Juan
2021	A*	`conf`	Adversarially Robust Low Dimensional Representations. COLT Pranjal Awasthi, Vaggos Chatziafratis, Xue Chen, Aravindan Vijayaraghavan
2021	A*	`conf`	Calibration and Consistency of Adversarial Surrogate Losses. NeurIPS Pranjal Awasthi, Natalie Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong
2021	J	`jnl`	Calibration and Consistency of Adversarial Surrogate Losses. CoRR Pranjal Awasthi, Natalie Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong
2021	A*	`conf`	Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations. NeurIPS Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan
2021	J	`jnl`	Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations. CoRR Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan
2021	—	`conf`	Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information. FAccT Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang
2021	J	`jnl`	Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information. CoRR Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang
2021	C	`conf`	Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. AIES Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
2021	J	`jnl`	Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. CoRR Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
2021	A*	`conf`	Neural Active Learning with Performance Guarantees. NeurIPS Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile
2021	J	`jnl`	Neural Active Learning with Performance Guarantees. CoRR Pranjal Awasthi, Christoph Dann, Claudio Gentile, Ayush Sekhari, Zhilei Wang
2021	A*	`conf`	On the Existence of The Adversarial Bayes Classifier. NeurIPS Pranjal Awasthi, Natalie Frank, Mehryar Mohri
2021	J	`jnl`	On the Existence of the Adversarial Bayes Classifier (Extended Version). CoRR Pranjal Awasthi, Natalie S. Frank, Mehryar Mohri
2021	J	`jnl`	On the benefits of maximum likelihood estimation for Regression and Forecasting. CoRR Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh
2021	J	`jnl`	Semi-supervised Active Regression. CoRR Devvrit, Nived Rajaraman, Pranjal Awasthi
2020	J	`jnl`	A Deep Conditioning Treatment of Neural Networks. CoRR Naman Agarwal, Pranjal Awasthi, Satyen Kale
2020	J	`jnl`	A Notion of Individual Fairness for Clustering. CoRR Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern
2020	—	`conf`	A case for Data Democratization. AMCIS Pranjal Awasthi, Jordana J. George
2020	J	`jnl`	Adaptive Sampling to Reduce Disparate Performance. CoRR Jacob D. Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Jie Zhang
2020	A*	`conf`	Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks. ICML Pranjal Awasthi, Natalie Frank, Mehryar Mohri
2020	J	`jnl`	Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks. CoRR Pranjal Awasthi, Natalie Frank, Mehryar Mohri
2020	J	`jnl`	Adversarial Robustness Across Representation Spaces. CoRR Pranjal Awasthi, George Yu, Chun-Sung Ferng, Andrew Tomkins, Da-Cheng Juan
2020	A*	`conf`	Adversarial robustness via robust low rank representations. NeurIPS Pranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan
2020	J	`jnl`	Adversarial robustness via robust low rank representations. CoRR Pranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan
2020	J	`jnl`	Beyond Individual and Group Fairness. CoRR Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri
2020	A*	`conf`	Efficient active learning of sparse halfspaces with arbitrary bounded noise. NeurIPS Chicheng Zhang, Jie Shen, Pranjal Awasthi
2020	J	`jnl`	Efficient active learning of sparse halfspaces with arbitrary bounded noise. CoRR Chicheng Zhang, Jie Shen, Pranjal Awasthi
2020	A	`conf`	Equalized odds postprocessing under imperfect group information. AISTATS Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern
2020	A*	`conf`	Estimating Principal Components under Adversarial Perturbations. COLT Pranjal Awasthi, Xue Chen, Aravindan Vijayaraghavan
2020	J	`jnl`	Estimating Principal Components under Adversarial Perturbations. CoRR Pranjal Awasthi, Xue Chen, Aravindan Vijayaraghavan
2020	J	`jnl`	On the Rademacher Complexity of Linear Hypothesis Sets. CoRR Pranjal Awasthi, Natalie Frank, Mehryar Mohri
2020	A*	`conf`	PAC-Bayes Learning Bounds for Sample-Dependent Priors. NeurIPS Pranjal Awasthi, Satyen Kale, Stefani Karp, Mehryar Mohri
2020	J	`jnl`	Robust vertex enumeration for convex hulls in high dimensions. Ann. Oper. Res. Pranjal Awasthi, Bahman Kalantari, Yikai Zhang
2020	C	`conf`	The Impact of Data Philanthropy on Global Health When Mediated Through Digital Epidemiology. ICIS Pranjal Awasthi, Jordana J. George
2019	J	`jnl`	Adversarially Robust Low Dimensional Representations. CoRR Pranjal Awasthi, Vaggos Chatziafratis, Xue Chen, Aravindan Vijayaraghavan
2019	A	`conf`	Bilu-Linial Stability, Certified Algorithms and the Independent Set Problem. ESA Haris Angelidakis, Pranjal Awasthi, Avrim Blum, Vaggos Chatziafratis, Chen Dan
2019	J	`jnl`	Effectiveness of Equalized Odds for Fair Classification under Imperfect Group Information. CoRR Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern
2019	A*	`conf`	Fair k-Center Clustering for Data Summarization. ICML Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern
2019	J	`jnl`	Fair k-Center Clustering for Data Summarization. CoRR Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern
2019	A*	`conf`	Guarantees for Spectral Clustering with Fairness Constraints. ICML Matthäus Kleindessner, Samira Samadi, Pranjal Awasthi, Jamie Morgenstern
2019	J	`jnl`	Guarantees for Spectral Clustering with Fairness Constraints. CoRR Matthäus Kleindessner, Samira Samadi, Pranjal Awasthi, Jamie Morgenstern
2019	A*	`conf`	On Robustness to Adversarial Examples and Polynomial Optimization. NeurIPS Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan
2019	J	`jnl`	On Robustness to Adversarial Examples and Polynomial Optimization. CoRR Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan
2019	J	`jnl`	On the adaptivity gap in two-stage robust linear optimization under uncertain packing constraints. Math. Program. Pranjal Awasthi, Vineet Goyal, Brian Y. Lu
2019	A*	`conf`	Robust Communication-Optimal Distributed Clustering Algorithms. ICALP Pranjal Awasthi, Ainesh Bakshi, Maria-Florina Balcan, Colin White, David P. Woodruff
2019	A	`conf`	Robust Matrix Completion from Quantized Observations. AISTATS Jie Shen, Pranjal Awasthi, Ping Li
2018	J	`jnl`	Bilu-Linial stability, certified algorithms and the Independent Set problem. CoRR Haris Angelidakis, Pranjal Awasthi, Avrim Blum, Vaggos Chatziafratis, Chen Dan
2018	A*	`conf`	Clustering Semi-Random Mixtures of Gaussians. ICML Pranjal Awasthi, Aravindan Vijayaraghavan
2018	A*	`conf`	Crowdsourcing with Arbitrary Adversaries. ICML Matthäus Kleindessner, Pranjal Awasthi
2018	A	`conf`	Robust Vertex Enumeration for Convex Hulls in High Dimensions. AISTATS Pranjal Awasthi, Bahman Kalantari, Yikai Zhang
2018	J	`jnl`	Robust Vertex Enumeration for Convex Hulls in High Dimensions. CoRR Pranjal Awasthi, Bahman Kalantari, Yikai Zhang
2018	A*	`conf`	Towards Learning Sparsely Used Dictionaries with Arbitrary Supports. FOCS Pranjal Awasthi, Aravindan Vijayaraghavan
2018	J	`jnl`	Towards Learning Sparsely Used Dictionaries with Arbitrary Supports. CoRR Pranjal Awasthi, Aravindan Vijayaraghavan
2017	J	`jnl`	Clustering Semi-Random Mixtures of Gaussians. CoRR Pranjal Awasthi, Aravindan Vijayaraghavan
2017	A*	`conf`	Efficient PAC Learning from the Crowd. COLT Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour
2017	J	`jnl`	Efficient PAC Learning from the Crowd. CoRR Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour
2017	J	`jnl`	General and Robust Communication-Efficient Algorithms for Distributed Clustering. CoRR Pranjal Awasthi, Maria-Florina Balcan, Colin White
2017	J	`jnl`	Local algorithms for interactive clustering. J. Mach. Learn. Res. Pranjal Awasthi, Maria-Florina Balcan, Konstantin Voevodski
2017	J	`jnl`	The Power of Localization for Efficiently Learning Linear Separators with Noise. J. ACM Pranjal Awasthi, Maria-Florina Balcan, Philip M. Long
2016	—	`ch.`	Clustering Under Stability Assumptions. Encyclopedia of Algorithms Pranjal Awasthi
2016	A*	`conf`	Learning and 1-bit Compressed Sensing under Asymmetric Noise. COLT Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Hongyang Zhang
2016	A	`conf`	Spectral Embedding of k-Cliques, Graph Partitioning and k-Means. ITCS Pranjal Awasthi, Moses Charikar, Ravishankar Krishnaswamy, Ali Kemal Sinop
2016	J	`jnl`	Testing Lipschitz Functions on Hypergrid Domains. Algorithmica Pranjal Awasthi, Madhav Jha, Marco Molinaro, Sofya Raskhodnikova
2015	A*	`conf`	Efficient Learning of Linear Separators under Bounded Noise. COLT Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner
2015	J	`jnl`	Efficient Learning of Linear Separators under Bounded Noise. CoRR Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner
2015	A*	`conf`	Label optimal regret bounds for online local learning. COLT Pranjal Awasthi, Moses Charikar, Kevin A. Lai, Andrej Risteski
2015	J	`jnl`	Label optimal regret bounds for online local learning. CoRR Pranjal Awasthi, Moses Charikar, Kevin A. Lai, Andrej Risteski
2015	—	`conf`	On some provably correct cases of variational inference for topic models. NIPS Pranjal Awasthi, Andrej Risteski
2015	J	`jnl`	On some provably correct cases of variational inference for topic models. CoRR Pranjal Awasthi, Andrej Risteski
2015	A	`conf`	Relax, No Need to Round: Integrality of Clustering Formulations. ITCS Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel A. Ward
2015	A*	`conf`	The Hardness of Approximation of Euclidean k-Means. SoCG Pranjal Awasthi, Moses Charikar, Ravishankar Krishnaswamy, Ali Kemal Sinop
2015	J	`jnl`	The Hardness of Approximation of Euclidean k-means. CoRR Pranjal Awasthi, Moses Charikar, Ravishankar Krishnaswamy, Ali Kemal Sinop
2014	—	`conf`	Learning Mixtures of Ranking Models. NIPS Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan
2014	J	`jnl`	Learning Mixtures of Ranking Models. CoRR Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan
2014	J	`jnl`	Limitations of Local Filters of Lipschitz and Monotone Functions. ACM Trans. Comput. Theory Pranjal Awasthi, Madhav Jha, Marco Molinaro, Sofya Raskhodnikova
2014	A*	`conf`	Local algorithms for interactive clustering. ICML Pranjal Awasthi, Maria-Florina Balcan, Konstantin Voevodski
2014	J	`jnl`	Relax, no need to round: integrality of clustering formulations. CoRR Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel A. Ward
2014	A*	`conf`	The power of localization for efficiently learning linear separators with noise. STOC Pranjal Awasthi, Maria-Florina Balcan, Philip M. Long
2013	—	`—`	Approximation Algorithms and New Models for Clustering and Learning. Pranjal Awasthi
2013	A*	`conf`	Learning Using Local Membership Queries. COLT Pranjal Awasthi, Vitaly Feldman, Varun Kanade
2013	J	`jnl`	Local algorithms for interactive clustering. CoRR Pranjal Awasthi, Maria-Florina Balcan, Konstantin Voevodski
2013	J	`jnl`	The Power of Localization for Efficiently Learning Linear Separators with Malicious Noise. CoRR Pranjal Awasthi, Maria-Florina Balcan, Philip M. Long
2012	J	`jnl`	Additive Approximation for Near-Perfect Phylogeny Construction CoRR Pranjal Awasthi, Avrim Blum, Jamie Morgenstern, Or Sheffet
2012	—	`conf`	Additive Approximation for Near-Perfect Phylogeny Construction. APPROX-RANDOM Pranjal Awasthi, Avrim Blum, Jamie Morgenstern, Or Sheffet
2012	J	`jnl`	Center-based clustering under perturbation stability. Inf. Process. Lett. Pranjal Awasthi, Avrim Blum, Or Sheffet
2012	J	`jnl`	Improved Spectral-Norm Bounds for Clustering CoRR Pranjal Awasthi, Or Sheffet
2012	—	`conf`	Improved Spectral-Norm Bounds for Clustering. APPROX-RANDOM Pranjal Awasthi, Or Sheffet
2012	J	`jnl`	Learning using Local Membership Queries under Smooth Distributions CoRR Pranjal Awasthi, Varun Kanade
2012	—	`conf`	Limitations of Local Filters of Lipschitz and Monotone Functions. APPROX-RANDOM Pranjal Awasthi, Madhav Jha, Marco Molinaro, Sofya Raskhodnikova
2012	J	`jnl`	Limitations of Local Filters of Lipschitz and Monotone Functions. Electron. Colloquium Comput. Complex. Pranjal Awasthi, Madhav Jha, Marco Molinaro, Sofya Raskhodnikova
2012	—	`conf`	Testing Lipschitz Functions on Hypergrid Domains. APPROX-RANDOM Pranjal Awasthi, Madhav Jha, Marco Molinaro, Sofya Raskhodnikova
2012	J	`jnl`	Testing Lipschitz Functions on Hypergrid Domains. Electron. Colloquium Comput. Complex. Pranjal Awasthi, Madhav Jha, Marco Molinaro, Sofya Raskhodnikova
2011	J	`jnl`	Decision trees for entity identification: Approximation algorithms and hardness results. ACM Trans. Algorithms Venkatesan T. Chakaravarthy, Vinayaka Pandit, Sambuddha Roy, Pranjal Awasthi, Mukesh K. Mohania
2010	J	`jnl`	Center-based Clustering under Perturbation Stability CoRR Pranjal Awasthi, Avrim Blum, Or Sheffet
2010	A*	`conf`	Improved Guarantees for Agnostic Learning of Disjunctions. COLT Pranjal Awasthi, Avrim Blum, Or Sheffet
2010	B	`conf`	On Nash-Equilibria of Approximation-Stable Games. SAGT Pranjal Awasthi, Maria-Florina Balcan, Avrim Blum, Or Sheffet, Santosh S. Vempala
2010	A*	`conf`	Stability Yields a PTAS for k-Median and k-Means Clustering. FOCS Pranjal Awasthi, Avrim Blum, Or Sheffet
2010	—	`conf`	Supervised Clustering. NIPS Pranjal Awasthi, Reza Bosagh Zadeh
2009	A*	`conf`	Online Stochastic Optimization in the Large: Application to Kidney Exchange. IJCAI Pranjal Awasthi, Tuomas Sandholm
2007	A*	`conf`	Decision trees for entity identification: approximation algorithms and hardness results. PODS Venkatesan T. Chakaravarthy, Vinayaka Pandit, Sambuddha Roy, Pranjal Awasthi, Mukesh K. Mohania
2007	A*	`conf`	Image Modeling Using Tree Structured Conditional Random Fields. IJCAI Pranjal Awasthi, Aakanksha Gagrani, Balaraman Ravindran