31 citations · 103 across the 21 of their papers we have counts for
22 papers
Sampling-Based Optimization for Multi-Agent Model Predictive Control
Ziyi Wang, Augustinos D. Saravanos, Hassan Almubarak +2
We systematically review the Variational Optimization, Variational Inference and Stochastic Search perspectives on sampling-based dynamic optimization and discuss their connections…
Deep Graphic FBSDEs for Opinion Dynamics Stochastic Control
Tianrong Chen, Ziyi Wang, Evangelos A. Theodorou
In this paper, we present a scalable deep learning approach to solve opinion dynamics stochastic optimal control problems with mean field term coupling in the dynamics and cost fun…
Opinion Dynamics Steering using Stochastic Search
Ziyi Wang, Evangelos A. Theodorou
In this paper, we apply the stochastic search dynamic optimization framework for steering opinion dynamics in a partially active population. The framework is grounded on stochastic…
Stochastic optimization for learning quantum state feedback control
Ethan N. Evans, Ziyi Wang, Adam G. Frim +2
High fidelity state preparation represents a fundamental challenge in the application of quantum technology. While the majority of optimal control approaches use feedback to improv…
Maximum Entropy Differential Dynamic Programming
Oswin So, Ziyi Wang, Evangelos A. Theodorou
In this paper, we present a novel maximum entropy formulation of the Differential Dynamic Programming algorithm and derive two variants using unimodal and multimodal value function…
LibFewShot: A Comprehensive Library for Few-shot Learning
Wenbin Li, Ziyi, Wang +9
Few-shot learning, especially few-shot image classification, has received increasing attention and witnessed significant advances in recent years. Some recent studies implicitly sh…
Spatial-Temporal Deep Intention Destination Networks for Online Travel Planning
Yu Li, Fei Xiong, Ziyi Wang +4
Nowadays, artificial neural networks are widely used for users' online travel planning. Personalized travel planning has many real applications and is affected by various factors,…
LHRM: A LBS based Heterogeneous Relations Model for User Cold Start Recommendation in Online Travel Platform
Ziyi Wang, Wendong Xiao, Yu Li +2
Most current recommender systems used the historical behaviour data of user to predict user' preference. However, it is difficult to recommend items to new users accurately. To all…
Itinerary-aware Personalized Deep Matching at Fliggy
Jia Xu, Ziyi Wang, Zulong Chen +3
Matching items for a user from a travel item pool of large cardinality have been the most important technology for increasing the business at Fliggy, one of the most popular online…
Variational Inference MPC using Tsallis Divergence
Ziyi Wang, Oswin So, Jason Gibson +4
In this paper, we provide a generalized framework for Variational Inference-Stochastic Optimal Control by using thenon-extensive Tsallis divergence. By incorporating the deformed e…
Learning in Nonzero-Sum Stochastic Games with Potentials
David Mguni, Yutong Wu, Yali Du +6
Multi-agent reinforcement learning (MARL) has become effective in tackling discrete cooperative game scenarios. However, MARL has yet to penetrate settings beyond those modelled by…
Large-Scale Multi-Agent Deep FBSDEs
Tianrong Chen, Ziyi Wang, Ioannis Exarchos +1
In this paper we present a scalable deep learning framework for finding Markovian Nash Equilibria in multi-agent stochastic games using fictitious play. The motivation is inspired…
Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs
Marcus Aloysius Pereira, Ziyi Wang, Ioannis Exarchos +1
This paper introduces a new formulation for stochastic optimal control and stochastic dynamic optimization that ensures safety with respect to state and control constraints. The pr…
Adaptive Risk Sensitive Model Predictive Control with Stochastic Search
Ziyi Wang, Oswin So, Keuntaek Lee +2
We present a general framework for optimizing the Conditional Value-at-Risk for dynamical systems using stochastic search. The framework is capable of handling the uncertainty from…
NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-End Learning and Control
Ioannis Exarchos, Marcus A. Pereira, Ziyi Wang +1
In this work we propose the use of adaptive stochastic search as a building block for general, non-convex optimization operations within deep neural network architectures. Specific…
Constrained Sampling-based Trajectory Optimization using Stochastic Approximation
George I. Boutselis, Ziyi Wang, Evangelos A. Theodorou
We propose a sampling-based trajectory optimization methodology for constrained problems. We extend recent works on stochastic search to deal with box control constraints,as well a…
Deep Forward-Backward SDEs for Min-max Control
Ziyi Wang, Keuntaek Lee, Marcus A. Pereira +2
This paper presents a novel approach to numerically solve stochastic differential games for nonlinear systems. The proposed approach relies on the nonlinear Feynman-Kac theorem tha…
Deep 2FBSDEs For Systems With Control Multiplicative Noise
Marcus A Pereira, Ziyi Wang, Tianrong Chen +2
We present a deep recurrent neural network architecture to solve a class of stochastic optimal control problems described by fully nonlinear Hamilton Jacobi Bellmanpartial differen…
Learning Deep Stochastic Optimal Control Policies using Forward-Backward SDEs
Marcus Pereira, Ziyi Wang, Ioannis Exarchos +1
In this paper we propose a new methodology for decision-making under uncertainty using recent advancements in the areas of nonlinear stochastic optimal control theory, applied math…
Ensemble Bayesian Decision Making with Redundant Deep Perceptual Control Policies
Keuntaek Lee, Ziyi Wang, Bogdan I. Vlahov +2
This work presents a novel ensemble of Bayesian Neural Networks (BNNs) for control of safety-critical systems. Decision making for safety-critical systems is challenging due to per…
Information Theoretic Model Predictive Control on Jump Diffusion Processes
Ziyi Wang, Grady Williams, Evangelos A. Theodorou
In this paper we present an information theoretic approach to stochastic optimal control problems for systems with compound Poisson noise. We generalize previous work on informatio…
A novel unsteady aerodynamic Reduced-Order Modeling method for transonic aeroelastic optimization
Ziyi Wang, Weiwei Zhang, Xiaojing Wu +1
In aircraft design, structural optimization and uncertainty quantification concerning transonic aeroelastic issues are computationally impractical, because the iterative process re…