Search Results for author: Yuxiang Yang

Found 13 papers, 4 papers with code

Fast and Efficient Locomotion via Learned Gait Transitions

1 code implementation9 Apr 2021 Yuxiang Yang, Tingnan Zhang, Erwin Coumans, Jie Tan, Byron Boots

We focus on the problem of developing energy efficient controllers for quadrupedal robots.

ES-ENAS: Blackbox Optimization over Hybrid Spaces via Combinatorial and Continuous Evolution

1 code implementation19 Jan 2021 Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Daiyi Peng, Deepali Jain, Wenbo Gao, Aldo Pacchiano, Tamas Sarlos, Yuxiang Yang

We consider the problem of efficient blackbox optimization over a large hybrid search space, consisting of a mixture of a high dimensional continuous space and a complex combinatorial space.

Combinatorial Optimization Continuous Control +3

Representation matching for delegated quantum computing

no code implementations14 Sep 2020 Yuxiang Yang, Masahito Hayashi

Many quantum computational tasks have inherent symmetries, suggesting a path to enhancing their efficiency and performance.

Quantum Physics

Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning

no code implementations2 Mar 2020 Xingyou Song, Yuxiang Yang, Krzysztof Choromanski, Ken Caluwaerts, Wenbo Gao, Chelsea Finn, Jie Tan

Learning adaptable policies is crucial for robots to operate autonomously in our complex and quickly changing world.

Legged Robots Meta-Learning

A unified framework of predicting binary interestingness of images based on discriminant correlation analysis and multiple kernel learning

no code implementations14 Oct 2019 Qiang Sun, Liting Wang, Maohui Li, Longtao Zhang, Yuxiang Yang

In the modern content-based image retrieval systems, there is an increasingly interest in constructing a computationally effective model to predict the interestingness of images since the measure of image interestingness could improve the human-centered search satisfaction and the user experience in different applications.

Content-Based Image Retrieval

Reinforcement Learning with Chromatic Networks

no code implementations25 Sep 2019 Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Wenbo Gao, Aldo Pacchiano, Tamas Sarlos, Deepali Jain, Yuxiang Yang

We present a neural architecture search algorithm to construct compact reinforcement learning (RL) policies, by combining ENAS and ES in a highly scalable and intuitive way.

Neural Architecture Search

ES-MAML: Simple Hessian-Free Meta Learning

1 code implementation ICLR 2020 Xingyou Song, Wenbo Gao, Yuxiang Yang, Krzysztof Choromanski, Aldo Pacchiano, Yunhao Tang

We introduce ES-MAML, a new framework for solving the model agnostic meta learning (MAML) problem based on Evolution Strategies (ES).

Meta-Learning

Reinforcement Learning with Chromatic Networks for Compact Architecture Search

no code implementations10 Jul 2019 Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Wenbo Gao, Aldo Pacchiano, Tamas Sarlos, Deepali Jain, Yuxiang Yang

We present a neural architecture search algorithm to construct compact reinforcement learning (RL) policies, by combining ENAS and ES in a highly scalable and intuitive way.

Combinatorial Optimization Neural Architecture Search

Data Efficient Reinforcement Learning for Legged Robots

no code implementations8 Jul 2019 Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Tingnan Zhang, Jie Tan, Vikas Sindhwani

We present a model-based framework for robot locomotion that achieves walking based on only 4. 5 minutes (45, 000 control steps) of data collected on a quadruped robot.

Legged Robots Safe Exploration

Quantum Compression of Tensor Network States

no code implementations14 Apr 2019 Ge Bai, Yuxiang Yang, Giulio Chiribella

We design quantum compression algorithms for parametric families of tensor network states.

Quantum Physics

Provably Robust Blackbox Optimization for Reinforcement Learning

no code implementations7 Mar 2019 Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Deepali Jain, Yuxiang Yang, Atil Iscen, Jasmine Hsu, Vikas Sindhwani

Interest in derivative-free optimization (DFO) and "evolutionary strategies" (ES) has recently surged in the Reinforcement Learning (RL) community, with growing evidence that they can match state of the art methods for policy optimization problems in Robotics.

Text-to-Image Generation

NoRML: No-Reward Meta Learning

1 code implementation4 Mar 2019 Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Jie Tan, Chelsea Finn

To this end, we introduce a method that allows for self-adaptation of learned policies: No-Reward Meta Learning (NoRML).

Meta-Learning

Deep Time-Frequency Representation and Progressive Decision Fusion for ECG Classification

no code implementations19 Jan 2019 Jing Zhang, Jing Tian, Yang Cao, Yuxiang Yang, Xiaobin Xu

Early recognition of abnormal rhythms in ECG signals is crucial for monitoring and diagnosing patients' cardiac conditions, increasing the success rate of the treatment.

ECG Classification General Classification

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