output
20092026
most citedTransductive Multi-view Zero-Shot Learning

551 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing cs.LGShow all

6 papers · 1 filter

cs.LG2021★ 1 cited

Exploiting the Hidden Tasks of GANs: Making Implicit Subproblems Explicit

Romann M. Weber

We present an alternative perspective on the training of generative adversarial networks (GANs), showing that the training step for a GAN generator decomposes into two implicit sub…

cs.LG2017★ 83 cited

Deep Scattering: Rendering Atmospheric Clouds with Radiance-Predicting Neural Networks

Simon Kallweit, Thomas Müller, Brian McWilliams +2

We present a technique for efficiently synthesizing images of atmospheric clouds using a combination of Monte Carlo integration and neural networks. The intricacies of Lorenz-Mie s…

cs.LG2017★ 13 cited

Determinantal Point Processes for Mini-Batch Diversification

Cheng Zhang, Hedvig Kjellstrom, Stephan Mandt

We study a mini-batch diversification scheme for stochastic gradient descent (SGD). While classical SGD relies on uniformly sampling data points to form a mini-batch, we propose a…

cs.LG2017★ 56 cited

Coordinated Multi-Agent Imitation Learning

Hoang M. Le, Yisong Yue, Peter Carr +1

We study the problem of imitation learning from demonstrations of multiple coordinating agents. One key challenge in this setting is that learning a good model of coordination can…

cs.LG2016★ 14 cited

Smooth Imitation Learning for Online Sequence Prediction

Hoang M. Le, Andrew Kang, Yisong Yue +1

We study the problem of smooth imitation learning for online sequence prediction, where the goal is to train a policy that can smoothly imitate demonstrated behavior in a dynamic a…

cs.LG2015★ 8 cited

The Boundary Forest Algorithm for Online Supervised and Unsupervised Learning

Charles Mathy, Nate Derbinsky, José Bento +2

We describe a new instance-based learning algorithm called the Boundary Forest (BF) algorithm, that can be used for supervised and unsupervised learning. The algorithm builds a for…