午後のarXiv

のcs.NE, cs.LG, cs.AI, cs.CV, cs.CL, stat.MLに投稿された毎日の論文を、日本時間の正午から10分間隔でツイートするbotです。試験運用中。

[午後のarXiv @arxivml]

"Looking at the posterior: on the origin of uncertainty in neural-network classification",
H． Linander, O． Balabano…
https://t.co/QjxL0jB3Mg

[午後のarXiv @arxivml]

"Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective",
Sébastien Lachapelle, Tristan …
https://t.co/gUwJt84aZg

[午後のarXiv @arxivml]

"A Theoretical Study of Inductive Biases in Contrastive Learning",
Jeff Z． HaoChen, Tengyu Ma
https://t.co/XFyV8D7LQi

[午後のarXiv @arxivml]

"Constrained Pure Exploration Multi-Armed Bandits with a Fixed Budget",
Fathima Zarin Faizal, Jayakrishnan Nair
https://t.co/cGPRvG5OCY

[午後のarXiv @arxivml]

"Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs",
Guangru…
https://t.co/teHZGliTlp

[午後のarXiv @arxivml]

"Domain Generalization for Robust Model-Based Offline Reinforcement Learning",
Alan Clark, Shoaib Ahmed Siddiqui, R…
https://t.co/zIrHDer7Ks

[午後のarXiv @arxivml]

"Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions",
Juan L． Ga…
https://t.co/qhqxviw5yT

[午後のarXiv @arxivml]

"A Permutation-free Kernel Two-Sample Test",
Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas
https://t.co/47gMIPRonq

[午後のarXiv @arxivml]

"Label Alignment Regularization for Distribution Shift",
Ehsan Imani, Guojun Zhang, Jun Luo, Pascal Poupart, Yangch…
https://t.co/eGkjLtqPDf

[午後のarXiv @arxivml]

"Online Kernel CUSUM for Change-Point Detection",
Song Wei, Yao Xie
https://t.co/PRXmBEznhH

[午後のarXiv @arxivml]

"Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls",
Yiping Lu, Jiajin Li, Lex…
https://t.co/DssdLVo62M

[午後のarXiv @arxivml]

"Transductive Kernels for Gaussian Processes on Graphs",
Yin-Cong Zhi, Felix L． Opolka, Yin Cheng Ng, Pietro Liò, X…
https://t.co/PufABZ1MQP

[午後のarXiv @arxivml]

"Copula Density Neural Estimation",
Nunzio A． Letizia, Andrea M． Tonello
https://t.co/xLIfrMUGc6

[午後のarXiv @arxivml]

"Causal Deep Reinforcement Learning using Observational Data",
Wenxuan Zhu, Chao Yu, Qiang Zhang
https://t.co/5n6OgxIOkL

[午後のarXiv @arxivml]

"Incentive-Aware Recommender Systems in Two-Sided Markets",
Xiaowu Dai, Yuan, Michael I． Jordan
https://t.co/0zTPfDQji6

[午後のarXiv @arxivml]

"Lightning Fast Video Anomaly Detection via Adversarial Knowledge Distillation",
Nicolae-Catalin Ristea, Florinel-A…
https://t.co/nANL0N6UWw

[午後のarXiv @arxivml]

"Optimal Approximation Rates for Deep ReLU Neural Networks on Sobolev Spaces",
Jonathan W． Siegel
https://t.co/MnrnJ7QSES

[午後のarXiv @arxivml]

"Distribution Free Prediction Sets for Node Classification",
Jase Clarkson
https://t.co/6w65BPgRl5

[午後のarXiv @arxivml]

"Transfer learning with high-dimensional quantile regression",
Jiayu Huang, Mingqiu Wang, Yuanshan Wu
https://t.co/iHS1HXj7hS

[午後のarXiv @arxivml]

"Convergence Rate Analysis for Optimal Computing Budget Allocation Algorithms",
Yanwen Li, Siyang Gao
https://t.co/CwORCNQHwJ