Machine Learning

Authors and titles for recent submissions

• Thu, 2 May 2024
• Wed, 1 May 2024
• Tue, 30 Apr 2024
• Mon, 29 Apr 2024
• Fri, 26 Apr 2024

Thu, 2 May 2024

[1]  arXiv:2405.00642 [pdf, other]

Title: From Empirical Observations to Universality: Dynamics of Deep Learning with Inputs Built on Gaussian mixture

Authors: Jaeyong Bae, Hawoong Jeong

Comments: 19 pages, 9 figures

Subjects: Machine Learning (stat.ML); Disordered Systems and Neural Networks (cond-mat.dis-nn); Statistical Mechanics (cond-mat.stat-mech); Machine Learning (cs.LG)

[2]  arXiv:2405.00592 [pdf, other]

Title: Scaling and renormalization in high-dimensional regression

Authors: Alexander B. Atanasov, Jacob A. Zavatone-Veth, Cengiz Pehlevan

Comments: 64 pages, 16 figures

Subjects: Machine Learning (stat.ML); Disordered Systems and Neural Networks (cond-mat.dis-nn); Machine Learning (cs.LG)

[3]  arXiv:2405.00442 [pdf, other]

Title: Geometric Insights into Focal Loss: Reducing Curvature for Enhanced Model Calibration

Authors: Masanari Kimura, Hiroki Naganuma

Comments: This paper is under consideration at Pattern Recognition Letters

Subjects: Machine Learning (stat.ML); Artificial Intelligence (cs.AI); Machine Learning (cs.LG)

[4]  arXiv:2405.00385 [pdf, other]

Title: Variational Bayesian Methods for a Tree-Structured Stick-Breaking Process Mixture of Gaussians

Authors: Yuta Nakahara

Subjects: Machine Learning (stat.ML); Information Theory (cs.IT); Machine Learning (cs.LG)

[5]  arXiv:2405.00675 (cross-list from cs.LG) [pdf, other]

Title: Self-Play Preference Optimization for Language Model Alignment

Authors: Yue Wu, Zhiqing Sun, Huizhuo Yuan, Kaixuan Ji, Yiming Yang, Quanquan Gu

Comments: 25 pages, 4 figures, 5 tables

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (stat.ML)

[6]  arXiv:2405.00454 (cross-list from cs.LG) [pdf, ps, other]

Title: Robust Semi-supervised Learning via $f$-Divergence and $α$-Rényi Divergence

Authors: Gholamali Aminian, Amirhossien Bagheri, Mahyar JafariNodeh, Radmehr Karimian, Mohammad-Hossein Yassaee

Comments: Accepted in ISIT 2024

Subjects: Machine Learning (cs.LG); Information Theory (cs.IT); Machine Learning (stat.ML)

[7]  arXiv:2405.00424 (cross-list from econ.EM) [pdf, other]

Title: Optimal Bias-Correction and Valid Inference in High-Dimensional Ridge Regression: A Closed-Form Solution

Authors: Zhaoxing Gao

Comments: 53 pages, 10 figures

Subjects: Econometrics (econ.EM); Methodology (stat.ME); Machine Learning (stat.ML)

[8]  arXiv:2405.00417 (cross-list from cs.LG) [pdf, other]

Title: Conformal Risk Control for Ordinal Classification

Authors: Yunpeng Xu, Wenge Guo, Zhi Wei

Comments: 17 pages, 8 figures, 2 table; 1 supplementary page

Journal-ref: In UAI 2023: The 39th Conference on Uncertainty in Artificial Intelligence

Subjects: Machine Learning (cs.LG); Methodology (stat.ME); Machine Learning (stat.ML)

[9]  arXiv:2405.00202 (cross-list from cs.LG) [pdf, other]

Title: Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design

Authors: A N M Nafiz Abeer, Sanket Jantre, Nathan M Urban, Byung-Jun Yoon

Subjects: Machine Learning (cs.LG); Quantitative Methods (q-bio.QM); Machine Learning (stat.ML)

[10]  arXiv:2405.00172 (cross-list from cs.LG) [pdf, other]

Title: Re-visiting Skip-Gram Negative Sampling: Dimension Regularization for More Efficient Dissimilarity Preservation in Graph Embeddings

Authors: David Liu, Arjun Seshadri, Tina Eliassi-Rad, Johan Ugander

Subjects: Machine Learning (cs.LG); Social and Information Networks (cs.SI); Machine Learning (stat.ML)

[11]  arXiv:2405.00158 (cross-list from stat.ME) [pdf, other]

Title: BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python

Authors: Nathaniel Haines, Conor Goold

Subjects: Methodology (stat.ME); Machine Learning (cs.LG); Machine Learning (stat.ML)

[12]  arXiv:2405.00129 (cross-list from cs.SI) [pdf, other]

Title: Complex contagions can outperform simple contagions for network reconstruction with dense networks or saturated dynamics

Authors: Nicholas W. Landry, William Thompson, Laurent Hébert-Dufresne, Jean-Gabriel Young

Comments: 8 pages, 5 figures

Subjects: Social and Information Networks (cs.SI); Populations and Evolution (q-bio.PE); Machine Learning (stat.ML)

[13]  arXiv:2405.00081 (cross-list from math.PR) [pdf, other]

Title: Imprecise Markov Semigroups and their Ergodicity

Authors: Michele Caprio

Subjects: Probability (math.PR); Statistics Theory (math.ST); Machine Learning (stat.ML)

[14]  arXiv:2405.00065 (cross-list from math.OC) [pdf, other]

Title: From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization

Authors: Mohammad Pedramfar, Vaneet Aggarwal

Subjects: Optimization and Control (math.OC); Computational Complexity (cs.CC); Machine Learning (cs.LG); Machine Learning (stat.ML)

[15]  arXiv:2405.00017 (cross-list from cs.DC) [pdf, other]

Title: Queuing dynamics of asynchronous Federated Learning

Authors: Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines

Subjects: Distributed, Parallel, and Cluster Computing (cs.DC); Machine Learning (cs.LG); Machine Learning (stat.ML)

Wed, 1 May 2024 (showing first 10 of 21 entries)

[16]  arXiv:2404.19557 [pdf, other]

Title: Neural Dynamic Data Valuation

Authors: Zhangyong Liang, Huanhuan Gao, Ji Zhang

Comments: 43 pages, 19 figures

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[17]  arXiv:2404.19301 [pdf, ps, other]

Title: Statistics and explainability: a fruitful alliance

Authors: Valentina Ghidini

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[18]  arXiv:2404.19220 [pdf, other]

Title: Regression for matrix-valued data via Kronecker products factorization

Authors: Yin-Jen Chen, Minh Tang

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[19]  arXiv:2404.19157 [pdf, other]

Title: Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks

Authors: Javier Antoran

Comments: PhD Thesis, University of Cambridge

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[20]  arXiv:2404.19073 [pdf, other]

Title: Learning Sparse High-Dimensional Matrix-Valued Graphical Models From Dependent Data

Authors: Jitendra K Tugnait

Comments: 16 pages, 2 figures, 1 table

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Signal Processing (eess.SP)

[21]  arXiv:2404.19756 (cross-list from cs.LG) [pdf, other]

Title: KAN: Kolmogorov-Arnold Networks

Authors: Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson, Marin Soljačić, Thomas Y. Hou, Max Tegmark

Comments: 48 pages, 20 figures. Codes are available at this https URL

Subjects: Machine Learning (cs.LG); Disordered Systems and Neural Networks (cond-mat.dis-nn); Artificial Intelligence (cs.AI); Machine Learning (stat.ML)

[22]  arXiv:2404.19719 (cross-list from cs.LG) [pdf, other]

Title: The lazy (NTK) and rich ($μ$P) regimes: a gentle tutorial

Authors: Dhruva Karkada

Comments: 22 pages, 7 figures

Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)

[23]  arXiv:2404.19661 (cross-list from stat.ME) [pdf, other]

Title: PCA for Point Processes

Authors: Franck Picard, Vincent Rivoirard, Angelina Roche, Victor Panaretos

Subjects: Methodology (stat.ME); Machine Learning (stat.ML)

[24]  arXiv:2404.19649 (cross-list from cs.LG) [pdf, other]

Title: Landmark Alternating Diffusion

Authors: Sing-Yuan Yeh, Hau-Tieng Wu, Ronen Talmon, Mao-Pei Tsui

Subjects: Machine Learning (cs.LG); Statistics Theory (math.ST); Data Analysis, Statistics and Probability (physics.data-an); Machine Learning (stat.ML)

[25]  arXiv:2404.19640 (cross-list from cs.LG) [pdf, other]

Title: Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks

Authors: Yunzhen Feng, Tim G. J. Rudner, Nikolaos Tsilivis, Julia Kempe

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Methodology (stat.ME); Machine Learning (stat.ML)

• Thu, 2 May 2024
• Wed, 1 May 2024
• Tue, 30 Apr 2024
• Mon, 29 Apr 2024
• Fri, 26 Apr 2024