:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Yoo, Jaesung, Lemke, Stefan, Guo, Jian Zhong, Rajan, Kanaka, Hantman, Adam
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning
Accès en ligne:	https://arxiv.org/abs/2605.01066
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A Variational Manifold Embedding Framework for Nonlinear Dimensionality Reduction
par: Vastola, John J., et autres
Publié: (2025)

Gradient Descent as Loss Landscape Navigation: a Normative Framework for Deriving Learning Rules
par: Vastola, John J., et autres
Publié: (2025)

AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research
par: Simmons-Edler, Riley, et autres
Publié: (2024)

Measuring and Controlling Solution Degeneracy across Task-Trained Recurrent Neural Networks
par: Huang, Ann, et autres
Publié: (2024)

Dual policy as self-model for planning
par: Yoo, Jaesung, et autres
Publié: (2023)

CTSR: Cartesian tensor-based sparse regression for data-driven discovery of high-dimensional invariant governing equations
par: Zhang, Boqian, et autres
Publié: (2025)

InputDSA: Demixing then Comparing Recurrent and Externally Driven Dynamics
par: Huang, Ann, et autres
Publié: (2025)

Semantics-Aware Generative Latent Data Augmentation for Learning in Low-Resource Domains
par: Bae, Jaesung, et autres
Publié: (2026)

Unsupervised Reservoir Computing for Multivariate Denoising of Severely Contaminated Signals
par: Choi, Jaesung, et autres
Publié: (2024)

On metric choice in dimension reduction for Fréchet regression
par: Soale, Abdul-Nasah, et autres
Publié: (2024)

POCO: Scalable Neural Forecasting through Population Conditioning
par: Duan, Yu, et autres
Publié: (2025)

Cost-constrained multi-label group feature selection using shadow features
par: Klonecki, Tomasz, et autres
Publié: (2024)

Signal-noise separation using unsupervised reservoir computing
par: Choi, Jaesung, et autres
Publié: (2024)

Something from Nothing: Data Augmentation for Robust Severity Level Estimation of Dysarthric Speech
par: Bae, Jaesung, et autres
Publié: (2026)

Critical Patch-Aware Sparse Prompting with Decoupled Training for Continual Learning on the Edge
par: Lim, Wonseon, et autres
Publié: (2026)

Deep RL Needs Deep Behavior Analysis: Exploring Implicit Planning by Model-Free Agents in Open-Ended Environments
par: Simmons-Edler, Riley, et autres
Publié: (2025)

Fréchet random forests for metric space valued regression with non euclidean predictors
par: Capitaine, Louis, et autres
Publié: (2019)

Statistical Methodology in the Social Sciences: Searching the Literature on DIALOG.
par: Hantman, Carl S.
Publié: (1983)

Prevalidated ridge regression is a highly-efficient drop-in replacement for logistic regression for high-dimensional data
par: Dempster, Angus, et autres
Publié: (2024)

On the good reliability of an interval-based metric to validate prediction uncertainty for machine learning regression tasks
par: Pernot, Pascal
Publié: (2024)

Character-aware audio-visual subtitling in context
par: Huh, Jaesung, et autres
Publié: (2024)

Heterogeneous transfer learning for high-dimensional regression with feature mismatch
par: Chang, Jae Ho, et autres
Publié: (2024)

Scaling and renormalization in high-dimensional regression
par: Atanasov, Alexander, et autres
Publié: (2024)

ALTBI: Constructing Improved Outlier Detection Models via Optimization of Inlier-Memorization Effect
par: Cho, Seoyoung, et autres
Publié: (2024)

Support estimation in high-dimensional heteroscedastic mean regression
par: Hermann, Philipp, et autres
Publié: (2020)

Features are fate: a theory of transfer learning in high-dimensional regression
par: Tahir, Javan, et autres
Publié: (2024)

On Evaluation of Unsupervised Feature Selection for Pattern Classification
par: Kim, Gyu-Il, et autres
Publié: (2026)

Sparse deep neural networks for nonparametric estimation in high-dimensional sparse regression
par: Wu, Dongya, et autres
Publié: (2024)

Minimax optimal transfer learning for high-dimensional additive regression
par: Moon, Seung Hyun
Publié: (2025)

High-dimensional censored MIDAS logistic regression for corporate survival forecasting
par: Miao, Wei, et autres
Publié: (2025)

From Memories to Maps: Mechanisms of In-Context Reinforcement Learning in Transformers
par: Fang, Ching, et autres
Publié: (2025)

A variational Bayes approach to debiased inference for low-dimensional parameters in high-dimensional linear regression
par: Castillo, Ismaël, et autres
Publié: (2024)

Convex estimation of Gaussian graphical regression models with covariates
par: Liu, Ruobin, et autres
Publié: (2024)

Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction
par: Fard, Sina Aghaee Dabaghan, et autres
Publié: (2025)

Parametric Mean-Field empirical Bayes in high-dimensional linear regression
par: Lee, Seunghyun, et autres
Publié: (2026)

Debiased high-dimensional regression calibration for errors-in-variables log-contrast models
par: Zhao, Huali, et autres
Publié: (2024)

High-dimensional logistic regression with missing data: Imputation, regularization, and universality
par: Verchand, Kabir Aladin, et autres
Publié: (2024)

Variational empirical Bayes variable selection in high-dimensional logistic regression
par: Tang, Yiqi, et autres
Publié: (2025)

Local regression on path spaces with signature metrics
par: Bayer, Christian, et autres
Publié: (2025)

An approach to Fisher-Rao metric for infinite dimensional non-parametric information geometry
par: Cheng, Bing, et autres
Publié: (2025)