Papers
LogME: Practical Assessment of Pre-trained Models for Transfer Learning
Kaichao You, Yong Liu, Jianmin Wang et al.
Lossless Compression of Efficient Private Local Randomizers
Vitaly Feldman, Kunal Talwar
Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling
Gregory Benton, Wesley Maddox, Sanae Lotfi et al.
Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?
Ning Liu, Geng Yuan, Zhengping Che et al.
Lower-Bounded Proper Losses for Weakly Supervised Classification
Shuhei M Yoshida, Takashi Takenouchi, Masashi Sugiyama
Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag et al.
Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision
Johan Björck, Xiangyu Chen, Christopher De Sa et al.
Low-Rank Sinkhorn Factorization
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
LTL2Action: Generalizing LTL Instructions for Multi-Task RL
Pashootan Vaezipoor, Andrew C Li, Rodrigo A Toro Icarte et al.
Machine Unlearning for Random Forests
Jonathan Brophy, Daniel Lowd
Making Paper Reviewing Robust to Bid Manipulation Attacks
Ruihan Wu, Chuan Guo, Felix Wu et al.
Making transport more robust and interpretable by moving data through a small number of anchor points
Chi-Heng Lin, Mehdi Azabou, Eva Dyer
Mandoline: Model Evaluation under Distribution Shift
Mayee Chen, Karan Goel, Nimit S Sohoni et al.
Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data
Amnon Catav, Boyang Fu, Yazeed Zoabi et al.
Marginalized Stochastic Natural Gradients for Black-Box Variational Inference
Geng Ji, Debora Sujono, Erik B Sudderth
MARINA: Faster Non-Convex Distributed Learning with Compression
Eduard Gorbunov, Konstantin P. Burlachenko, Zhize Li et al.
Markpainting: Adversarial Machine Learning meets Inpainting
David Khachaturov, Ilia Shumailov, Yiren Zhao et al.
Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling
Kuruge Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin et al.
Matrix Completion with Model-free Weighting
Jiayi Wang, Raymond K. W. Wong, Xiaojun Mao et al.
Matrix Sketching for Secure Collaborative Machine Learning
Mengjiao Zhang, Shusen Wang
Maximum Mean Discrepancy Test is Aware of Adversarial Attacks
Ruize Gao, Feng Liu, Jingfeng Zhang et al.
MC-LSTM: Mass-Conserving LSTM
Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz et al.
Measuring Robustness in Deep Learning Based Compressive Sensing
Mohammad Zalbagi Darestani, Akshay S Chaudhari, Reinhard Heckel
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences
Ikko Yamane, Junya Honda, Florian Yger et al.
Megaverse: Simulating Embodied Agents at One Million Experiences per Second
Aleksei Petrenko, Erik Wijmans, Brennan Shacklett et al.