Papers
Littlestone Classes are Privately Online Learnable
Noah Golowich, Roi Livni
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes
Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan et al.
Local Differential Privacy for Regret Minimization in Reinforcement Learning
Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke et al.
Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization
Travers Rhodes, Daniel D. Lee
Local Explanation of Dialogue Response Generation
Yi-Lin Tuan, Connor Pryor, Wenhu Chen et al.
Local Hyper-Flow Diffusion
Kimon Fountoulakis, Pan Li, Shenghao Yang
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios
Alessandro Favero, Francesco Cagnetta, Matthieu Wyart
Locality Sensitive Teaching
Zhaozhuo Xu, Beidi Chen, Chaojian Li et al.
Localization, Convexity, and Star Aggregation
Suhas Vijaykumar
Localization with Sampling-Argmax
Jiefeng Li, Tong Chen, Ruiqi Shi et al.
Locally differentially private estimation of functionals of discrete distributions
Cristina Butucea, Yann ISSARTEL
Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models
Keunseo Kim, JunCheol Shin, Heeyoung Kim
Locally private online change point detection
Tom Berrett, Yi Yu
Locally Valid and Discriminative Prediction Intervals for Deep Learning Models
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Local plasticity rules can learn deep representations using self-supervised contrastive predictions
Bernd Illing, Jean Ventura, Guillaume Bellec et al.
Local policy search with Bayesian optimization
Sarah Müller, Alexander von Rohr, Sebastian Trimpe
Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels
Stefani Karp, Ezra Winston, Yuanzhi Li et al.
Logarithmic Regret from Sublinear Hints
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar et al.
Logarithmic Regret in Feature-based Dynamic Pricing
Jianyu Xu, Yu-Xiang Wang
Long Short-Term Transformer for Online Action Detection
Mingze Xu, Yuanjun Xiong, Hao Chen et al.
Long-Short Transformer: Efficient Transformers for Language and Vision
Chen Zhu, Wei Ping, Chaowei Xiao et al.
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis
Thomas FEL, Remi Cadene, Mathieu Chalvidal et al.
Look at What I’m Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos
Reuben Tan, Bryan Plummer, Kate Saenko et al.
Looking Beyond Single Images for Contrastive Semantic Segmentation Learning
FEIHU ZHANG, Philip Torr, Rene Ranftl et al.
Loss function based second-order Jensen inequality and its application to particle variational inference
Futoshi Futami, Tomoharu Iwata, naonori ueda et al.