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Yulong Zhou

Publications and source records attributed to Yulong Zhou.

4 recordsLinked to original sources

Duality and approximation of stochastic optimal control problems under expectation constraints

We consider a continuous time stochastic optimal control problem under both equality and inequality constraints on the expectation of some functionals of the controlled process. Under a qualification condition, we show that the problem is in duality with an optimization problem involving the Lagrange multiplier associated with the constraints. Then by convex analysis techniques, we provide a general existence result and some a priori estimation of the dual optimizers. We further provide a necessary and sufficient optimality condition for the initial constrained control problem. The same results are also obtained for a discrete time constrained control problem. Moreover, under additional regularity conditions, it is proved that the discrete time control problem converges to the continuous time problem, possibly with a convergence rate. This convergence result can be used to obtain numerical algorithms to approximate the continuous time control problem, which we illustrate by two simple numerical examples.

math.OC

DELTA: A DEep learning based Language Technology plAtform

In this paper we present DELTA, a deep learning based language technology platform. DELTA is an end-to-end platform designed to solve industry level natural language and speech processing problems. It integrates most popular neural network models for training as well as comprehensive deployment tools for production. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. We demonstrate the reliable performance with DELTA on several natural language processing and speech tasks, including text classification, named entity recognition, natural language inference, speech recognition, speaker verification, etc. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users.

cs.CL

High order approximation for the Boltzmann equation without angular cutoff

In order to solve the Boltzmann equation numerically, in the present work, we propose a new model equation to approximate the Boltzmann equation without angular cutoff. Here the approximate equation incorporates Boltzmann collision operator with angular cut-off and the Landau collision operator. As a first step, we prove the well-posedness theory for our approximate equation. Then in the next step we show the error estimate between the solutions to the approximate equation and the original equation. Compared to the standard angular cut-off approximation method, our method results in higher order of accuracy.

math.AP

Event-based Bipartite Consensus on Signed Networks

In this paper, a bipartite consensus problem for a multi-agent system is formulated firstly. Then an event-based interaction rule is proposed for the multi-agent system with antagonistic interactions. The bipartite consensus stability is analyzed on the basis of spectral properties of the signed Laplacian matrix associated with multi-agent networks. Some simulation results are presented to illustrate the bipartite consensus with the proposed interaction rule.

nlin.AO