Dravyansh Sharma

43 papers A* 12A 7Journal 24
YearRankTypeTitle / Venue / Authors
2026 J jnl
Online Learnability of Chain-of-Thought Verifiers: Soundness and Completeness Trade-offs.
CoRR
Maria-Florina Balcan, Avrim Blum, Kiriaki Fragkia, Zhiyuan Li, Dravyansh Sharma
2025 J jnl
Algorithm Configuration for Structured Pfaffian Settings.
Trans. Mach. Learn. Res.
Maria-Florina Balcan, Anh Tuan Nguyen, Dravyansh Sharma
2025 J jnl
Algorithm Design and Stronger Guarantees for the Improving Multi-Armed Bandits Problem.
CoRR
Avrim Blum, Marten Garicano, Kavya Ravichandran, Dravyansh Sharma
2025 J jnl
Conservative classifiers do consistently well with improving agents: characterizing statistical and online learning.
CoRR
Dravyansh Sharma, Alec Sun
2025 J jnl
Distribution-dependent Generalization Bounds for Tuning Linear Regression Across Tasks.
CoRR
Maria-Florina Balcan, Saumya Goyal, Dravyansh Sharma
2025 J jnl
Gradient Descent with Provably Tuned Learning-rate Schedules.
CoRR
Dravyansh Sharma
2025 A* conf
Learning Accurate and Interpretable Decision Trees (Extended Abstract).
IJCAI
Maria-Florina Balcan, Dravyansh Sharma
2025 A* conf
Offline-to-Online Hyperparameter Transfer for Stochastic Bandits.
AAAI
Dravyansh Sharma, Arun Suggala
2025 J jnl
Offline-to-online hyperparameter transfer for stochastic bandits.
CoRR
Dravyansh Sharma, Arun Sai Suggala
2025 J jnl
On Learning Verifiers for Chain-of-Thought Reasoning.
CoRR
Maria-Florina Balcan, Avrim Blum, Zhiyuan Li, Dravyansh Sharma
2025 A* conf
PAC Learning with Improvements.
ICML
Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma, Matthew R. Walter
2025 J jnl
PAC Learning with Improvements.
CoRR
Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma, Matthew R. Walter
2025 J jnl
Sample complexity of data-driven tuning of model hyperparameters in neural networks with structured parameter-dependent dual function.
CoRR
Maria-Florina Balcan, Anh Tuan Nguyen, Dravyansh Sharma
2025 A conf
Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees.
UAI
Ally Yalei Du, Eric Huang, Dravyansh Sharma
2025 J jnl
Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees.
CoRR
Ally Yalei Du, Eric Huang, Dravyansh Sharma
2024 A* conf
Accelerating ERM for data-driven algorithm design using output-sensitive techniques.
NeurIPS
Maria-Florina Balcan, Christopher Seiler, Dravyansh Sharma
2024 A conf
Learning Accurate and Interpretable Decision Trees.
UAI
Maria-Florina Balcan, Dravyansh Sharma
2024 J jnl
Learning accurate and interpretable decision trees.
CoRR
Maria-Florina Balcan, Dravyansh Sharma
2024 A* conf
No Internal Regret with Non-convex Loss Functions.
AAAI
Dravyansh Sharma
2024 J jnl
Provable Hyperparameter Tuning for Structured Pfaffian Settings.
CoRR
Maria-Florina Balcan, Anh Tuan Nguyen, Dravyansh Sharma
2024 J jnl
Subsidy design for better social outcomes.
CoRR
Maria-Florina Balcan, Matteo Pozzi, Dravyansh Sharma
2023 J jnl
An Analysis of Robustness of Non-Lipschitz Networks.
J. Mach. Learn. Res.
Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang
2023 J jnl
Efficiently Learning the Graph for Semi-supervised Learning.
CoRR
Dravyansh Sharma, Maxwell Jones
2023 A conf
Efficiently learning the graph for semi-supervised learning.
UAI
Dravyansh Sharma, Maxwell Jones
2023 A* conf
New Bounds for Hyperparameter Tuning of Regression Problems Across Instances.
NeurIPS
Maria-Florina Balcan, Anh Nguyen, Dravyansh Sharma
2023 J jnl
Reliable Learning for Test-time Attacks and Distribution Shift.
CoRR
Maria-Florina Balcan, Steve Hanneke, Rattana Pukdee, Dravyansh Sharma
2023 A* conf
Reliable learning in challenging environments.
NeurIPS
Maria-Florina Balcan, Steve Hanneke, Rattana Pukdee, Dravyansh Sharma
2022 J jnl
Faster algorithms for learning to link, align sequences, and price two-part tariffs.
CoRR
Maria-Florina Balcan, Christopher Seiler, Dravyansh Sharma
2022 A* conf
Provably tuning the ElasticNet across instances.
NeurIPS
Maria-Florina Balcan, Misha Khodak, Dravyansh Sharma, Ameet Talwalkar
2022 J jnl
Provably tuning the ElasticNet across instances.
CoRR
Maria-Florina Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar
2022 A* conf
Robustly-reliable learners under poisoning attacks.
COLT
Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma
2022 J jnl
Robustly-reliable learners under poisoning attacks.
CoRR
Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma
2021 J jnl
Data driven algorithms for limited labeled data learning.
CoRR
Maria-Florina Balcan, Dravyansh Sharma
2021 A* conf
Data driven semi-supervised learning.
NeurIPS
Maria-Florina Balcan, Dravyansh Sharma
2021 A* conf
Learning-to-learn non-convex piecewise-Lipschitz functions.
NeurIPS
Maria-Florina Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar
2021 J jnl
Learning-to-learn non-convex piecewise-Lipschitz functions.
CoRR
Maria-Florina Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar
2020 A conf
Learning piecewise Lipschitz functions in changing environments.
AISTATS
Dravyansh Sharma, Maria-Florina Balcan, Travis Dick
2020 J jnl
On the Power of Abstention and Data-Driven Decision Making for Adversarial Robustness.
CoRR
Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang
2019 A conf
Better Morphology Prediction for Better Speech Systems.
INTERSPEECH
Dravyansh Sharma, Melissa Wilson, Antoine Bruguier
2019 J jnl
Online optimization of piecewise Lipschitz functions in changing environments.
CoRR
Maria-Florina Balcan, Travis Dick, Dravyansh Sharma
2018 A conf
Dictionary Augmented Sequence-to-Sequence Neural Network for Grapheme to Phoneme Prediction.
INTERSPEECH
Antoine Bruguier, Anton Bakhtin, Dravyansh Sharma
2018 A conf
On Training and Evaluation of Grapheme-to-Phoneme Mappings with Limited Data.
INTERSPEECH
Dravyansh Sharma
2015 A* conf
On Greedy Maximization of Entropy.
ICML
Dravyansh Sharma, Ashish Kapoor, Amit Deshpande