Papers
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware
Florian Tramer, Dan Boneh
LEARNING FACTORIZED REPRESENTATIONS FOR OPEN-SET DOMAIN ADAPTATION
Mahsa Baktashmotlagh, Masoud Faraki, Tom Drummond et al.
Adversarial Domain Adaptation for Stable Brain-Machine Interfaces
Ali Farshchian, Juan A. Gallego, Joseph P. Cohen et al.
Supervised Policy Update for Deep Reinforcement Learning
Quan Vuong, Yiming Zhang, Keith W. Ross
Differentiable Learning-to-Normalize via Switchable Normalization
Ping Luo, Jiamin Ren, Zhanglin Peng et al.
M^3RL: Mind-aware Multi-agent Management Reinforcement Learning
Tianmin Shu, Yuandong Tian
Directed-Info GAIL: Learning Hierarchical Policies from Unsegmented Demonstrations using Directed Information
Mohit Sharma, Arjun Sharma, Nicholas Rhinehart et al.
Are adversarial examples inevitable?
Ali Shafahi, W. Ronny Huang, Christoph Studer et al.
An analytic theory of generalization dynamics and transfer learning in deep linear networks
Andrew K. Lampinen, Surya Ganguli
A rotation-equivariant convolutional neural network model of primary visual cortex
Alexander S. Ecker, Fabian H. Sinz, Emmanouil Froudarakis et al.
ANYTIME MINIBATCH: EXPLOITING STRAGGLERS IN ONLINE DISTRIBUTED OPTIMIZATION
Nuwan Ferdinand, Haider Al-Lawati, Stark Draper et al.
Generating Multiple Objects at Spatially Distinct Locations
Tobias Hinz, Stefan Heinrich, Stefan Wermter
Analysis of Quantized Models
Lu Hou, Ruiliang Zhang, James T. Kwok
Context-adaptive Entropy Model for End-to-end Optimized Image Compression
Jooyoung Lee, Seunghyun Cho, Seung-Kwon Beack
Practical lossless compression with latent variables using bits back coding
James Townsend, Thomas Bird, David Barber
Sample Efficient Imitation Learning for Continuous Control
Fumihiro Sasaki, Tetsuya Yohira, Atsuo Kawaguchi
Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection
Tue Le, Tuan Nguyen, Trung Le et al.
Sample Efficient Adaptive Text-to-Speech
Yutian Chen, Yannis Assael, Brendan Shillingford et al.
Distribution-Interpolation Trade off in Generative Models
Damian Leśniak, Igor Sieradzki, Igor Podolak
Conditional Network Embeddings
Bo Kang, Jefrey Lijffijt, Tijl De Bie
Deterministic Variational Inference for Robust Bayesian Neural Networks
Anqi Wu, Sebastian Nowozin, Edward Meeds et al.
Variance Networks: When Expectation Does Not Meet Your Expectations
Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha et al.
Learning to Remember More with Less Memorization
Hung Le, Truyen Tran, Svetha Venkatesh
DELTA: DEEP LEARNING TRANSFER USING FEATURE MAP WITH ATTENTION FOR CONVOLUTIONAL NETWORKS
Xingjian Li, Haoyi Xiong, Hanchao Wang et al.
signSGD via Zeroth-Order Oracle
Sijia Liu, Pin-Yu Chen, Xiangyi Chen et al.