Sharma, Dravyansh

22 publications

TMLR 2025 Algorithm Configuration for Structured Pfaffian Settings Maria Florina Balcan, Anh Tuan Nguyen, Dravyansh Sharma

NeurIPS 2025 Conservative Classifiers Do Consistently Well with Improving Agents: Characterizing Statistical and Online Learning Dravyansh Sharma, Alec Sun

IJCAI 2025 Learning Accurate and Interpretable Decision Trees (Extended Abstract) Maria-Florina Balcan, Dravyansh Sharma

AAAI 2025 Offline-to-Online Hyperparameter Transfer for Stochastic Bandits Dravyansh Sharma, Arun Sai Suggala

NeurIPS 2025 On Learning Verifiers and Implications to Chain-of-Thought Reasoning Maria Florina Balcan, Avrim Blum, Zhiyuan Li, Dravyansh Sharma

ICML 2025 PAC Learning with Improvements Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma, Matthew Walter

NeurIPS 2025 Sample Complexity of Data-Driven Tuning of Model Hyperparameters in Neural Networks with Structured Parameter-Dependent Dual Function Maria Florina Balcan, Anh Tuan Nguyen, Dravyansh Sharma

UAI 2025 Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees Ally Yalei Du, Eric Huang, Dravyansh Sharma

NeurIPS 2024 Accelerating ERM for Data-Driven Algorithm Design Using Output-Sensitive Techniques Maria-Florina Balcan, Christopher Seiler, Dravyansh Sharma

UAI 2024 Learning Accurate and Interpretable Decision Trees Maria-Florina Balcan, Dravyansh Sharma

AAAI 2024 No Internal Regret with Non-Convex Loss Functions Dravyansh Sharma

ICMLW 2024 Theoretical Analyses of Hyperparameter Selection in Graph-Based Semi-Supervised Learning Ally Yalei Du, Eric Huang, Dravyansh Sharma

JMLR 2023 An Analysis of Robustness of Non-Lipschitz Networks Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang

UAI 2023 Efficiently Learning the Graph for Semi-Supervised Learning Dravyansh Sharma, Maxwell Jones

NeurIPS 2023 New Bounds for Hyperparameter Tuning of Regression Problems Across Instances Maria-Florina F Balcan, Anh Nguyen, Dravyansh Sharma

NeurIPS 2023 Reliable Learning in Challenging Environments Maria-Florina F Balcan, Steve Hanneke, Rattana Pukdee, Dravyansh Sharma

NeurIPS 2022 Provably Tuning the ElasticNet Across Instances Maria-Florina F Balcan, Misha Khodak, Dravyansh Sharma, Ameet Talwalkar

COLT 2022 Robustly-Reliable Learners Under Poisoning Attacks Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma

NeurIPS 2021 Data Driven Semi-Supervised Learning Maria-Florina F Balcan, Dravyansh Sharma

NeurIPS 2021 Learning-to-Learn Non-Convex Piecewise-Lipschitz Functions Maria-Florina F Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar

AISTATS 2020 Learning Piecewise Lipschitz Functions in Changing Environments Dravyansh Sharma, Maria-Florina Balcan, Travis Dick

ICML 2015 On Greedy Maximization of Entropy Dravyansh Sharma, Ashish Kapoor, Amit Deshpande