Papers
KDEformer: Accelerating Transformers via Kernel Density Estimation
Amir Zandieh, Insu Han, Majid Daliri et al.
Kernel Logistic Regression Approximation of an Understandable ReLU Neural Network
Marie Guyomard, Susana Barbosa, Lionel Fillatre
Kernel QuantTree
Diego Stucchi, Paolo Rizzo, Nicolò Folloni et al.
Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data via Amalgamation
Junyoung Park, Jeongyoun Ahn, Cheolwoo Park
K-SHAP: Policy Clustering Algorithm for Anonymous Multi-Agent State-Action Pairs
Andrea Coletta, Svitlana Vyetrenko, Tucker Balch
Label differential privacy and private training data release
Robert Istvan Busa-Fekete, Andres Munoz Medina, Umar Syed et al.
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity
Dixian Zhu, Yiming Ying, Tianbao Yang
Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning
Amin Karbasi, Nikki Lijing Kuang, Yian Ma et al.
Language Instructed Reinforcement Learning for Human-AI Coordination
Hengyuan Hu, Dorsa Sadigh
Large Language Models Can Be Easily Distracted by Irrelevant Context
Freda Shi, Xinyun Chen, Kanishka Misra et al.
Large Language Models Struggle to Learn Long-Tail Knowledge
Nikhil Kandpal, Haikang Deng, Adam Roberts et al.
Last Switch Dependent Bandits with Monotone Payoff Functions
Ayoub Foussoul, Vineet Goyal, Orestis Papadigenopoulos et al.
Latent Traversals in Generative Models as Potential Flows
Yue Song, T. Anderson Keller, Nicu Sebe et al.
Layered State Discovery for Incremental Autonomous Exploration
Liyu Chen, Andrea Tirinzoni, Alessandro Lazaric et al.
Lazy Agents: A New Perspective on Solving Sparse Reward Problem in Multi-agent Reinforcement Learning
Boyin Liu, Zhiqiang Pu, Yi Pan et al.
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation
Rui Xue, Haoyu Han, Mohamadali Torkamani et al.
LeadFL: Client Self-Defense against Model Poisoning in Federated Learning
Chaoyi Zhu, Stefanie Roos, Lydia Y. Chen
Learnability and Algorithm for Continual Learning
Gyuhak Kim, Changnan Xiao, Tatsuya Konishi et al.
Learning Affinity with Hyperbolic Representation for Spatial Propagation
Jin-Hwi Park, Jaesung Choe, Inhwan Bae et al.
Learning Antidote Data to Individual Unfairness
Peizhao Li, Ethan Xia, Hongfu Liu
Learning-augmented private algorithms for multiple quantile release
Mikhail Khodak, Kareem Amin, Travis Dick et al.
Learning Belief Representations for Partially Observable Deep RL
Andrew Wang, Andrew C Li, Toryn Q. Klassen et al.
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction
Youwei Liang, Kevin Stone, Ali Shameli et al.
Learning Control by Iterative Inversion
Gal Leibovich, Guy Jacob, Or Avner et al.
Learning Controllable Degradation for Real-World Super-Resolution via Constrained Flows
Seobin Park, Dongjin Kim, Sungyong Baik et al.