:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Medvedev, Marko, Lyu, Kaifeng, Li, Zhiyuan, Srebro, Nathan
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2510.25108
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Weak-to-Strong Generalization Even in Random Feature Networks, Provably
di: Medvedev, Marko, et al.
Pubblicazione: (2025)

Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality
di: Medvedev, Marko, et al.
Pubblicazione: (2024)

Positive Distribution Shift as a Framework for Understanding Tractable Learning
di: Medvedev, Marko, et al.
Pubblicazione: (2026)

Recursive Models for Long-Horizon Reasoning
di: Yang, Chenxiao, et al.
Pubblicazione: (2026)

PENCIL: Long Thoughts with Short Memory
di: Yang, Chenxiao, et al.
Pubblicazione: (2025)

Quantifying Overfitting along the Regularization Path for Two-Part-Code MDL in Supervised Classification
di: Zhu, Xiaohan, et al.
Pubblicazione: (2025)

Data Mixing Can Induce Phase Transitions in Knowledge Acquisition
di: Gu, Xinran, et al.
Pubblicazione: (2025)

Noisy Interpolation Learning with Shallow Univariate ReLU Networks
di: Joshi, Nirmit, et al.
Pubblicazione: (2023)

Overfitting and Generalizing with (PAC) Bayesian Prediction in Noisy Binary Classification
di: Zhu, Xiaohan, et al.
Pubblicazione: (2026)

On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
di: Joshi, Nirmit, et al.
Pubblicazione: (2024)

Tight Bounds on the Binomial CDF, and the Minimum of i.i.d Binomials, in terms of KL-Divergence
di: Zhu, Xiaohan, et al.
Pubblicazione: (2025)

The Implicit Bias of Gradient Descent on Separable Data
di: Soudry, Daniel, et al.
Pubblicazione: (2017)

Research Program: Theory of Learning in Dynamical Systems
di: Hazan, Elad, et al.
Pubblicazione: (2025)

The Price of Implicit Bias in Adversarially Robust Generalization
di: Tsilivis, Nikolaos, et al.
Pubblicazione: (2024)

The Marginal Value of Momentum for Small Learning Rate SGD
di: Wang, Runzhe, et al.
Pubblicazione: (2023)

A Theory of Learning with Autoregressive Chain of Thought
di: Joshi, Nirmit, et al.
Pubblicazione: (2025)

An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
di: Zhou, Lijia, et al.
Pubblicazione: (2023)

On the Hardness of Learning Regular Expressions
di: Attias, Idan, et al.
Pubblicazione: (2025)

Learning single-index models via harmonic decomposition
di: Joshi, Nirmit, et al.
Pubblicazione: (2025)

Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes
di: Harel, Itamar, et al.
Pubblicazione: (2025)

Depth Separation in Norm-Bounded Infinite-Width Neural Networks
di: Parkinson, Suzanna, et al.
Pubblicazione: (2024)

Adam Reduces a Unique Form of Sharpness: Theoretical Insights Near the Minimizer Manifold
di: Li, Xinghan, et al.
Pubblicazione: (2025)

Online Bandits with (Biased) Offline Data: Adaptive Learning under Distribution Mismatch
di: Cheung, Wang Chi, et al.
Pubblicazione: (2024)

Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
di: Lyu, Kaifeng, et al.
Pubblicazione: (2023)

Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks
di: Li, Binghui, et al.
Pubblicazione: (2024)

Learning to Think from Multiple Thinkers
di: Joshi, Nirmit, et al.
Pubblicazione: (2026)

Score Design for Multi-Criteria Incentivization
di: Kabra, Anmol, et al.
Pubblicazione: (2024)

Mixed-feature Logistic Regression Robust to Distribution Shifts
di: Sun, Qingshi, et al.
Pubblicazione: (2025)

Learning to Answer from Correct Demonstrations
di: Joshi, Nirmit, et al.
Pubblicazione: (2025)

The Alignment Ceiling: Objective Mismatch in Reinforcement Learning from Human Feedback
di: Lambert, Nathan, et al.
Pubblicazione: (2023)

How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers
di: Buzaglo, Gon, et al.
Pubblicazione: (2024)

Provable Tempered Overfitting of Minimal Nets and Typical Nets
di: Harel, Itamar, et al.
Pubblicazione: (2024)

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval
di: Wen, Kaiyue, et al.
Pubblicazione: (2024)

Dataset Distillers Are Good Label Denoisers In the Wild
di: Cheng, Lechao, et al.
Pubblicazione: (2024)

Cross-Domain Policy Adaptation by Capturing Representation Mismatch
di: Lyu, Jiafei, et al.
Pubblicazione: (2024)

From Continual Learning to SGD and Back: Better Rates for Continual Linear Models
di: Evron, Itay, et al.
Pubblicazione: (2025)

Metalearning with Very Few Samples Per Task
di: Aliakbarpour, Maryam, et al.
Pubblicazione: (2023)

On the SDEs and Scaling Rules for Adaptive Gradient Algorithms
di: Malladi, Sadhika, et al.
Pubblicazione: (2022)

Applying statistical learning theory to deep learning
di: Gerbelot, Cédric, et al.
Pubblicazione: (2023)

Understanding Uncertainty-based Active Learning Under Model Mismatch
di: Rahmati, Amir Hossein, et al.
Pubblicazione: (2024)