Papers
Kernel-Based Tests for Likelihood-Free Hypothesis Testing
Patrik Robert Gerber, Tianze Jiang, Yury Polyanskiy et al.
Kernelized Cumulants: Beyond Kernel Mean Embeddings
Patric Bonnier, Harald Oberhauser, Zoltan Szabo
Kernelized Reinforcement Learning with Order Optimal Regret Bounds
Sattar Vakili, Julia Olkhovskaya
Kernel Quadrature with Randomly Pivoted Cholesky
Ethan Epperly, Elvira Moreno
Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization
Clement Benard, Brian Staber, Sébastien Da Veiga
Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation
Zhangsihao Yang, Mengwei Ren, Kaize Ding et al.
Kiki or Bouba? Sound Symbolism in Vision-and-Language Models
Morris Alper, Hadar Averbuch-Elor
Kissing to Find a Match: Efficient Low-Rank Permutation Representation
Hannah Dröge, Zorah Lähner, Yuval Bahat et al.
k-Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy
Chenglin Fan, Ping Li, Xiaoyun Li
K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing
Shuai Li, Yingjie Zhang, Hongtu Zhu et al.
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks
Minki Kang, Seanie Lee, Jinheon Baek et al.
Knowledge-based in silico models and dataset for the comparative evaluation of mammography AI for a range of breast characteristics, lesion conspicuities and doses
Elena Sizikova, Niloufar Saharkhiz, Diksha Sharma et al.
Knowledge Diffusion for Distillation
Tao Huang, Yuan Zhang, Mingkai Zheng et al.
Knowledge Distillation for High Dimensional Search Index
Zepu Lu, Jin Chen, Defu Lian et al.
Knowledge Distillation Performs Partial Variance Reduction
Mher Safaryan, Alexandra Peste, Dan Alistarh
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors
Yong Liu, Chenyu Li, Jianmin Wang et al.
Koopman Kernel Regression
Petar Bevanda, Max Beier, Armin Lederer et al.
Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
Runa Eschenhagen, Alexander Immer, Richard Turner et al.
KuaiSim: A Comprehensive Simulator for Recommender Systems
Kesen Zhao, Shuchang Liu, Qingpeng Cai et al.
Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards
Hao Qin, Kwang-Sung Jun, Chicheng Zhang
L2T-DLN: Learning to Teach with Dynamic Loss Network
Zhaoyang Hai, Liyuan Pan, Xiabi Liu et al.
Label Correction of Crowdsourced Noisy Annotations with an Instance-Dependent Noise Transition Model
Hui GUO, Boyu Wang, Grace Yi
Label-efficient Segmentation via Affinity Propagation
Wentong Li, Yuqian Yuan, Song Wang et al.
Labeling Neural Representations with Inverse Recognition
Kirill Bykov, Laura Kopf, Shinichi Nakajima et al.
Label-Only Model Inversion Attacks via Knowledge Transfer
Bao-Ngoc Nguyen, Keshigeyan Chandrasegaran, Milad Abdollahzadeh et al.