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Publication search results
found 680 matches
- 2017
- Sheng Li, Yun Fu:
Matching on Balanced Nonlinear Representations for Treatment Effects Estimation. NIPS 2017: 929-939 - Jiajun Wu, Erika Lu, Pushmeet Kohli, Bill Freeman, Josh Tenenbaum:
Learning to See Physics via Visual De-animation. NIPS 2017: 153-164 - Rong Ge, Tengyu Ma:
On the Optimization Landscape of Tensor Decompositions. NIPS 2017: 3653-3663 - Ziyu Wang, Josh Merel, Scott E. Reed, Nando de Freitas, Gregory Wayne, Nicolas Heess:
Robust Imitation of Diverse Behaviors. NIPS 2017: 5320-5329 - Ping Li, Martin Slawski:
Simple strategies for recovering inner products from coarsely quantized random projections. NIPS 2017: 4567-4576 - Jiajun Wu, Yifan Wang, Tianfan Xue, Xingyuan Sun, Bill Freeman, Josh Tenenbaum:
MarrNet: 3D Shape Reconstruction via 2.5D Sketches. NIPS 2017: 540-550 - Lin Chen, Andreas Krause, Amin Karbasi:
Interactive Submodular Bandit. NIPS 2017: 141-152 - Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou:
Improved Dynamic Regret for Non-degenerate Functions. NIPS 2017: 732-741 - Liwei Wang, Alexander G. Schwing, Svetlana Lazebnik:
Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space. NIPS 2017: 5756-5766 - Yasin Abbasi-Yadkori, Peter L. Bartlett, Victor Gabillon:
Near Minimax Optimal Players for the Finite-Time 3-Expert Prediction Problem. NIPS 2017: 3033-3042 - Emmanuel Abbe, Sanjeev R. Kulkarni, Eun Jee Lee:
Nonbacktracking Bounds on the Influence in Independent Cascade Models. NIPS 2017: 1407-1416 - Jacob D. Abernethy, Jun-Kun Wang:
On Frank-Wolfe and Equilibrium Computation. NIPS 2017: 6584-6593 - Luigi Acerbi, Wei Ji:
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search. NIPS 2017: 1836-1846 - Alireza Aghasi, Afshin Abdi, Nam Nguyen, Justin Romberg:
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee. NIPS 2017: 3177-3186 - Shipra Agrawal, Randy Jia:
Optimistic posterior sampling for reinforcement learning: worst-case regret bounds. NIPS 2017: 1184-1194 - Eirikur Agustsson, Fabian Mentzer, Michael Tschannen, Lukas Cavigelli, Radu Timofte, Luca Benini, Luc Van Gool:
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations. NIPS 2017: 1141-1151 - Sungsoo Ahn, Michael Chertkov, Jinwoo Shin:
Gauging Variational Inference. NIPS 2017: 2881-2890 - Kartik Ahuja, William R. Zame, Mihaela van der Schaar:
DPSCREEN: Dynamic Personalized Screening. NIPS 2017: 1321-1332 - Laurence Aitchison, Lloyd Russell, Adam M. Packer, Jinyao Yan, Philippe Castonguay, Michael Häusser, Srinivas C. Turaga:
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit. NIPS 2017: 3486-3495 - Ahmet Alacaoglu, Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher:
Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization. NIPS 2017: 5852-5861 - Maximilian Alber, Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller, Fei Sha:
An Empirical Study on The Properties of Random Bases for Kernel Methods. NIPS 2017: 2763-2774 - Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, Milan Vojnovic:
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding. NIPS 2017: 1709-1720 - Stéphanie Allassonnière, Juliette Chevallier, Stephane Oudard:
Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data. NIPS 2017: 1152-1160 - Zeyuan Allen-Zhu, Elad Hazan, Wei Hu, Yuanzhi Li:
Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls. NIPS 2017: 6191-6200 - Noga Alon, Daniel Reichman, Igor Shinkar, Tal Wagner, Sebastian Musslick, Jonathan D. Cohen, Tom Griffiths, Biswadip Dey, Kayhan Özcimder:
A graph-theoretic approach to multitasking. NIPS 2017: 2100-2109 - Noga Alon, Moshe Babaioff, Yannai A. Gonczarowski, Yishay Mansour, Shay Moran, Amir Yehudayoff:
Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues. NIPS 2017: 1656-1665 - Jason M. Altschuler, Jonathan Weed, Philippe Rigollet:
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. NIPS 2017: 1964-1974 - Jose M. Alvarez, Mathieu Salzmann:
Compression-aware Training of Deep Networks. NIPS 2017: 856-867 - Luca Ambrogioni, Max Hinne, Marcel van Gerven, Eric Maris:
GP CaKe: Effective brain connectivity with causal kernels. NIPS 2017: 950-959 - Kareem Amin, Nan Jiang, Satinder Singh:
Repeated Inverse Reinforcement Learning. NIPS 2017: 1815-1824
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