"linear regression" Papers
16 papers found
Conference
Are Greedy Task Orderings Better Than Random in Continual Linear Regression?
Matan Tsipory, Ran Levinstein, Itay Evron et al.
NEURIPS 2025arXiv:2510.19941
1
citations
A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
Licong Lin, Song Mei
NEURIPS 2025arXiv:2503.17538
3
citations
Gradient correlation is a key ingredient to accelerate SGD with momentum
Julien Hermant, Marien Renaud, Jean-François Aujol et al.
ICLR 2025arXiv:2410.07870
3
citations
In-Context Occam’s Razor: How Transformers Prefer Simpler Hypotheses on the Fly
Puneesh Deora, Bhavya Vasudeva, Tina Behnia et al.
COLM 2025paper
2
citations
Robustness Auditing for Linear Regression: To Singularity and Beyond
Ittai Rubinstein, Samuel Hopkins
ICLR 2025arXiv:2410.07916
7
citations
Task Descriptors Help Transformers Learn Linear Models In-Context
Ruomin Huang, Rong Ge
ICLR 2025
3
citations
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
Omri Lev, Vishwak Srinivasan, Moshe Shenfeld et al.
NEURIPS 2025arXiv:2505.24603
2
citations
Trained Mamba Emulates Online Gradient Descent in In-Context Linear Regression
Jiarui Jiang, Wei Huang, Miao Zhang et al.
NEURIPS 2025arXiv:2509.23779
1
citations
Transformers Handle Endogeneity in In-Context Linear Regression
Haodong Liang, Krishna Balasubramanian, Lifeng Lai
ICLR 2025arXiv:2410.01265
4
citations
Transformers Learn to Implement Multi-step Gradient Descent with Chain of Thought
Jianhao Huang, Zixuan Wang, Jason Lee
ICLR 2025arXiv:2502.21212
22
citations
Agnostic Sample Compression Schemes for Regression
Idan Attias, Steve Hanneke, Aryeh Kontorovich et al.
ICML 2024spotlightarXiv:1810.01864
4
citations
An Analysis of Linear Time Series Forecasting Models
William Toner, Luke Darlow
ICML 2024arXiv:2403.14587
47
citations
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi et al.
ICML 2024arXiv:2410.08292
38
citations
Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond
Kyriakos Axiotis, Vincent Cohen-Addad, Monika Henzinger et al.
ICML 2024arXiv:2402.17327
16
citations
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses
Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni
ICML 2024spotlightarXiv:2402.04987
4
citations
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation
Gavin Brown, Krishnamurthy Dvijotham, Georgina Evans et al.
ICML 2024arXiv:2402.13531
11
citations