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In this study, the congestion control problem for multiple transmission control protocol/active queue management (TCP/AQM) networks with user datagram protocol (UDP) flows is investigated. Taking the UDP stream as the unknown interference and ...

The paper proves the minimax theorem for a specific class of functions that are defined on branching polylines in a linear space, not on convex subsets of a linear space. The existence of a saddle point for such functions does not follow directly ...

This assignment allows students to gain experience with AI gameplaying algorithms, implementing minimax and alpha-beta pruning and designing a utility function for measuring game states. The assignment uses Connect Four, a relatively simple fully-...

This research examines a two-player combinatorial game, Game of Thrones: Hand of the King, and applies several different techniques to develop an effective AI player for this game. We used several approaches including simple game state analysis, ...

Currently, there are few theoretical or practical approaches available for general nonlinear robust optimization. Moreover, the approaches that do exist impose restrictive assumptions on the problem structure. We present an adaptive bundle method for ...

We consider the problem of finding algorithms for controlling the bandwidth of an automatic system in a game setting, when one of the players (the main control system) tries to improve the quality of transients and the other (the information ...

Quantile regression is the task of estimating a speci_ed percentile response, such as the median (50th percentile), from a collection of known covariates. We study quantile regression with rectified linear unit (ReLU) neural networks as the chosen model ...

We present a unified framework for estimation and analysis of generalized additive models in high dimensions. The framework defines a large class of penalized regression estimators, encompassing many existing methods. An efficient computational algorithm ...

We consider a problem of manifold estimation from noisy observations. Many manifold learning procedures locally approximate a manifold by a weighted average over a small neighborhood. However, in the presence of large noise, the assigned weights become so ...

Like the notion of shape derivative, the topological derivative has proven to be both pertinent and useful from the theoretical and numerical points of view. While the shape derivative is a differential, the topological derivative obtained by expansion ...

Zero-sum stochastic games, henceforth stochastic games, are a classical model in game theory in which two opponents interact and the environment changes in response to the players’ behavior. The central solution concepts for these games are the discounted ...

We consider the problem of localizing a submatrix with larger-than-usual entry values inside a data matrix, without the prior knowledge of the submatrix size. We establish an optimization framework based on a multiscale scan statistic, and develop ...

We present a high-index optimization-based shrinking dimer (HiOSD) method to compute index-$k$ saddle points as a generalization of the optimization-based shrinking dimer method for index-1 saddle points [L. Zhang, Q. Du, and Z. Zheng, SIAM J. Sci. ...

We analyze the per unit-time infinite horizon average cost Markov control model, subject to a total variation distance ambiguity on the controlled process conditional distribution. This stochastic optimal control problem is formulated as a minimax ...

We construct a family of iterations for computing the principal square root of a square matrix $A$ using Zolotarev's rational minimax approximants of the square root function. We show that these rational functions obey a recursion, allowing one to ...

In this paper, we introduce a new, fast data assimilation algorithm for a 2D linear advection equation with divergence-free coefficients. We first apply the nodal discontinuous Galerkin (DG) method to discretize the advection equation and then employ a set ...

Several methods exist for electing committees of representatives and conducting multiple referenda based on approval voting. Recently, a family of rules for approval-based voting using ordered weighted averaging was proposed, ranging from a simple ...

In this paper, we consider the design problem of making the convergence of the bounded-input, multi-input iterative learning controller presented in our previous work robust to errors in the model-based value of the input-output Jacobian matrix via a ...

In this paper, we propose an algorithm for estimating parameters of a source term of a linear advection-diffusion equation with an uncertain advection-velocity field. First, we apply a minimax state estimation technique in order to reduce uncertainty ...

The problem of quickest change detection is studied, where there is an additional constraint on the cost of observations used before the change point and where the post-change distribution is composite. Minimax formulations are proposed for this problem. ...