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Found 6 papers, 4 papers with code
Learning to Elect
Voting systems have a wide range of applications including recommender systems, web search, product design and elections.
A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints
The theory of integral quadratic constraints (IQCs) allows the certification of exponential convergence of interconnected systems containing nonlinear or uncertain elements.
Regularized linear autoencoders recover the principal components, eventually
Our understanding of learning input-output relationships with neural nets has improved rapidly in recent years, but little is known about the convergence of the underlying representations, even in the simple case of linear autoencoders (LAEs).
Benchmarking Model-Based Reinforcement Learning
Model-based reinforcement learning (MBRL) is widely seen as having the potential to be significantly more sample efficient than model-free RL.
TimbreTron: A WaveNet(CycleGAN(CQT(Audio))) Pipeline for Musical Timbre Transfer
In this work, we address the problem of musical timbre transfer, where the goal is to manipulate the timbre of a sound sample from one instrument to match another instrument while preserving other musical content, such as pitch, rhythm, and loudness.
Deep Neural Networks for Improved, Impromptu Trajectory Tracking of Quadrotors
Trajectory tracking control for quadrotors is important for applications ranging from surveying and inspection, to film making.
