Papers
450 papers found
Discrete Graph Hashing
Wei Liu, Cun Mu, Sanjiv Kumar et al.
Training Very Deep Networks
Rupesh K Srivastava, Klaus Greff, Jürgen Schmidhuber
Copeland Dueling Bandits
Masrour Zoghi, Zohar S Karnin, Shimon Whiteson et al.
Deep Knowledge Tracing
Chris Piech, Jonathan Bassen, Jonathan Huang et al.
Deep Poisson Factor Modeling
Ricardo Henao, Zhe Gan, James Lu et al.
Deep Visual Analogy-Making
Scott E Reed, Yi Zhang, Yuting Zhang et al.
Deep Submodular Functions: Definitions and Learning
Brian W Dolhansky, Jeff A. Bilmes
Deep Learning Games
Dale Schuurmans, Martin A Zinkevich
Learning to learn by gradient descent by gradient descent
Marcin Andrychowicz, Misha Denil, Sergio Gómez et al.
Dualing GANs
Yujia Li, Alexander Schwing, Kuan-Chieh Wang et al.
Deep Hyperspherical Learning
Weiyang Liu, Yan-Ming Zhang, Xingguo Li et al.
Decoupling "when to update" from "how to update"
Eran Malach, Shai Shalev-Shwartz
Certified Defenses for Data Poisoning Attacks
Jacob Steinhardt, Pang Wei W Koh, Percy Liang
Dynamic-Depth Context Tree Weighting
Joao V Messias, Shimon Whiteson
Dynamic Revenue Sharing
Santiago Balseiro, Max Lin, Vahab Mirrokni et al.
Learning ReLUs via Gradient Descent
Mahdi Soltanolkotabi
Deep Subspace Clustering Networks
Pan Ji, Tong Zhang, Hongdong Li et al.
Deep Supervised Discrete Hashing
Qi Li, Zhenan Sun, Ran He et al.
Deep Sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh et al.
COLA: Decentralized Linear Learning
Lie He, An Bian, Martin Jaggi
Middle-Out Decoding
Shikib Mehri, Leonid Sigal
Deepcode: Feedback Codes via Deep Learning
Hyeji Kim, Yihan Jiang, Sreeram Kannan et al.
Scaling provable adversarial defenses
Eric Wong, Frank Schmidt, Jan Hendrik Metzen et al.
Step Size Matters in Deep Learning
Kamil Nar, Shankar Sastry
Dual Swap Disentangling
Zunlei Feng, Xinchao Wang, Chenglong Ke et al.