Papers
11,015 papers found
Learning to Represent Programs with Property Signatures
Augustus Odena, Charles Sutton
Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering
Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi et al.
Learning to solve the credit assignment problem
Benjamin James Lansdell, Prashanth Ravi Prakash, Konrad Paul Kording
Learning transport cost from subset correspondence
Ruishan Liu, Akshay Balsubramani, James Zou
Learn to Explain Efficiently via Neural Logic Inductive Learning
Yuan Yang, Le Song
Linear Symmetric Quantization of Neural Networks for Low-precision Integer Hardware
Xiandong Zhao, Ying Wang, Xuyi Cai et al.
Lipschitz constant estimation of Neural Networks via sparse polynomial optimization
Fabian Latorre, Paul Rolland, Volkan Cevher
Lite Transformer with Long-Short Range Attention
Zhanghao Wu*, Zhijian Liu*, Ji Lin et al.
Locality and Compositionality in Zero-Shot Learning
Tristan Sylvain, Linda Petrini, Devon Hjelm
Logic and the 2-Simplicial Transformer
James Clift, Dmitry Doryn, Daniel Murfet et al.
Lookahead: A Far-sighted Alternative of Magnitude-based Pruning
Sejun Park*, Jaeho Lee*, Sangwoo Mo et al.
Low-dimensional statistical manifold embedding of directed graphs
Thorben Funke, Tian Guo, Alen Lancic et al.
Low-Resource Knowledge-Grounded Dialogue Generation
Xueliang Zhao, Wei Wu, Chongyang Tao et al.
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius
Runtian Zhai, Chen Dan, Di He et al.
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
Caglar Gulcehre, Tom Le Paine, Bobak Shahriari et al.
Making Sense of Reinforcement Learning and Probabilistic Inference
Brendan O'Donoghue, Ian Osband, Catalin Ionescu
Masked Based Unsupervised Content Transfer
Ron Mokady, Sagie Benaim, Lior Wolf et al.
Massively Multilingual Sparse Word Representations
Gábor Berend
Mathematical Reasoning in Latent Space
Dennis Lee, Christian Szegedy, Markus Rabe et al.
Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning
Dexter R.R. Scobee, S. Shankar Sastry
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning
Qingfeng Lan, Yangchen Pan, Alona Fyshe et al.
Measuring and Improving the Use of Graph Information in Graph Neural Networks
Yifan Hou, Jian Zhang, James Cheng et al.
Measuring Compositional Generalization: A Comprehensive Method on Realistic Data
Daniel Keysers, Nathanael Schärli, Nathan Scales et al.
Measuring the Reliability of Reinforcement Learning Algorithms
Stephanie C.Y. Chan, Samuel Fishman, Anoop Korattikara et al.
MEMO: A Deep Network for Flexible Combination of Episodic Memories
Andrea Banino, Adrià Puigdomènech Badia, Raphael Köster et al.