Saved in:
| Main Authors: | Sharma, Dravyansh, Suggala, Arun Sai |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.02926 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sample complexity of data-driven tuning of model hyperparameters in neural networks with structured parameter-dependent dual function
by: Balcan, Maria-Florina, et al.
Published: (2025)
by: Balcan, Maria-Florina, et al.
Published: (2025)
Conservative classifiers do consistently well with improving agents: characterizing statistical and online learning
by: Sharma, Dravyansh, et al.
Published: (2025)
by: Sharma, Dravyansh, et al.
Published: (2025)
CDQuant: Greedy Coordinate Descent for Accurate LLM Quantization
by: Nair, Pranav Ajit, et al.
Published: (2024)
by: Nair, Pranav Ajit, et al.
Published: (2024)
Gradient Descent with Provably Tuned Learning-rate Schedules
by: Sharma, Dravyansh
Published: (2025)
by: Sharma, Dravyansh
Published: (2025)
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
by: Kumar, Ramnath, et al.
Published: (2023)
by: Kumar, Ramnath, et al.
Published: (2023)
Learning accurate and interpretable tree-based models
by: Balcan, Maria-Florina, et al.
Published: (2024)
by: Balcan, Maria-Florina, et al.
Published: (2024)
Improving Generalization via Meta-Learning on Hard Samples
by: Jain, Nishant, et al.
Published: (2024)
by: Jain, Nishant, et al.
Published: (2024)
Regret minimization in Linear Bandits with offline data via extended D-optimal exploration
by: Vijayan, Sushant, et al.
Published: (2025)
by: Vijayan, Sushant, et al.
Published: (2025)
Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees
by: Du, Ally Yalei, et al.
Published: (2025)
by: Du, Ally Yalei, et al.
Published: (2025)
Distribution-dependent Generalization Bounds for Tuning Linear Regression Across Tasks
by: Balcan, Maria-Florina, et al.
Published: (2025)
by: Balcan, Maria-Florina, et al.
Published: (2025)
Efficient Public Health Intervention Planning Using Decomposition-Based Decision-Focused Learning
by: Shah, Sanket, et al.
Published: (2024)
by: Shah, Sanket, et al.
Published: (2024)
Second Order Methods for Bandit Optimization and Control
by: Suggala, Arun, et al.
Published: (2024)
by: Suggala, Arun, et al.
Published: (2024)
Algorithm Design and Stronger Guarantees for the Improving Multi-Armed Bandits Problem
by: Blum, Avrim, et al.
Published: (2025)
by: Blum, Avrim, et al.
Published: (2025)
Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD
by: Das, Aniket, et al.
Published: (2024)
by: Das, Aniket, et al.
Published: (2024)
Accelerating ERM for data-driven algorithm design using output-sensitive techniques
by: Balcan, Maria-Florina, et al.
Published: (2022)
by: Balcan, Maria-Florina, et al.
Published: (2022)
Subsidy design for better social outcomes
by: Balcan, Maria-Florina, et al.
Published: (2024)
by: Balcan, Maria-Florina, et al.
Published: (2024)
Algorithm Configuration for Structured Pfaffian Settings
by: Balcan, Maria-Florina, et al.
Published: (2024)
by: Balcan, Maria-Florina, et al.
Published: (2024)
On Learning Verifiers and Implications to Chain-of-Thought Reasoning
by: Balcan, Maria-Florina, et al.
Published: (2025)
by: Balcan, Maria-Florina, et al.
Published: (2025)
Provably tuning the ElasticNet across instances
by: Balcan, Maria-Florina, et al.
Published: (2022)
by: Balcan, Maria-Florina, et al.
Published: (2022)
$μ$pscaling small models: Principled warm starts and hyperparameter transfer
by: Ma, Yuxin, et al.
Published: (2026)
by: Ma, Yuxin, et al.
Published: (2026)
Online Bidding under RoS Constraints without Knowing the Value
by: Vijayan, Sushant, et al.
Published: (2025)
by: Vijayan, Sushant, et al.
Published: (2025)
Bayesian Collaborative Bandits with Thompson Sampling for Improved Outreach in Maternal Health Program
by: Dasgupta, Arpan, et al.
Published: (2024)
by: Dasgupta, Arpan, et al.
Published: (2024)
Extreme bandits
by: Carpentier, Alexandra, et al.
Published: (2026)
by: Carpentier, Alexandra, et al.
Published: (2026)
Online Learnability of Chain-of-Thought Verifiers: Soundness and Completeness Trade-offs
by: Balcan, Maria-Florina, et al.
Published: (2026)
by: Balcan, Maria-Florina, et al.
Published: (2026)
Beyond algorithm hyperparameters: on preprocessing hyperparameters and associated pitfalls in machine learning applications
by: Sauer, Christina, et al.
Published: (2024)
by: Sauer, Christina, et al.
Published: (2024)
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates
by: Mei, Jincheng, et al.
Published: (2025)
by: Mei, Jincheng, et al.
Published: (2025)
Spectral bandits
by: Kocák, Tomáš, et al.
Published: (2026)
by: Kocák, Tomáš, et al.
Published: (2026)
Fast UCB-type algorithms for stochastic bandits with heavy and super heavy symmetric noise
by: Dorn, Yuriy, et al.
Published: (2024)
by: Dorn, Yuriy, et al.
Published: (2024)
Be aware of overfitting by hyperparameter optimization!
by: Tetko, Igor V., et al.
Published: (2024)
by: Tetko, Igor V., et al.
Published: (2024)
Active clustering with bandit feedback
by: Thuot, Victor, et al.
Published: (2024)
by: Thuot, Victor, et al.
Published: (2024)
Effect of hyperparameters on variable selection in random forests
by: Fouodo, Cesaire J. K., et al.
Published: (2023)
by: Fouodo, Cesaire J. K., et al.
Published: (2023)
Instance-dependent Stochastic Lipschitz bandit
by: Potfer, Marius, et al.
Published: (2026)
by: Potfer, Marius, et al.
Published: (2026)
Spectral bandits for smooth graph functions
by: Valko, Michal, et al.
Published: (2026)
by: Valko, Michal, et al.
Published: (2026)
Approximate information maximization for bandit games
by: Barbier-Chebbah, Alex, et al.
Published: (2023)
by: Barbier-Chebbah, Alex, et al.
Published: (2023)
Online learning in bandits with predicted context
by: Guo, Yongyi, et al.
Published: (2023)
by: Guo, Yongyi, et al.
Published: (2023)
PAC Learning with Improvements
by: Attias, Idan, et al.
Published: (2025)
by: Attias, Idan, et al.
Published: (2025)
HELLINGER-UCB: A novel algorithm for stochastic multi-armed bandit problem and cold start problem in recommender system
by: Yang, Ruibo, et al.
Published: (2024)
by: Yang, Ruibo, et al.
Published: (2024)
Selecting time-series hyperparameters with the artificial jackknife
by: Pellegrino, Filippo
Published: (2020)
by: Pellegrino, Filippo
Published: (2020)
Calibrating dimension reduction hyperparameters in the presence of noise
by: Lin, Justin, et al.
Published: (2023)
by: Lin, Justin, et al.
Published: (2023)
Risk and optimal policies in bandit experiments
by: Adusumilli, Karun
Published: (2021)
by: Adusumilli, Karun
Published: (2021)
Similar Items
-
Sample complexity of data-driven tuning of model hyperparameters in neural networks with structured parameter-dependent dual function
by: Balcan, Maria-Florina, et al.
Published: (2025) -
Conservative classifiers do consistently well with improving agents: characterizing statistical and online learning
by: Sharma, Dravyansh, et al.
Published: (2025) -
CDQuant: Greedy Coordinate Descent for Accurate LLM Quantization
by: Nair, Pranav Ajit, et al.
Published: (2024) -
Gradient Descent with Provably Tuned Learning-rate Schedules
by: Sharma, Dravyansh
Published: (2025) -
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
by: Kumar, Ramnath, et al.
Published: (2023)