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We study the dynamic query evaluation problem: Given a full conjunctive query Q and a sequence of updates to the input database, we construct a data structure that supports constant-delay enumeration of the tuples in the query output after each update.

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This article analyzes the theoretical and methodological provisions of seminal works concerning the efficiency of research, development and development management, and production for hi-tech products in the context of uncertainty in order to make ...

The task of managing unstable systems is a critically important management problem, as an unstable object can pose significant danger to humans and the environment when it fails. In this paper, a neural network was trained to determine the ...

Divide and conquer algorithm is a common strategy applied in big data. Model averaging has the natural divide-and-conquer feature, but its theory has not been developed in big data scenarios. The goal of this paper is to fill this gap. We propose two ...

Bilevel optimization has recently attracted growing interests due to its wide applications in modern machine learning problems. Although recent studies have characterized the convergence rate for several such popular algorithms, it is still unclear how ...

In practical application, in order to make the solution obtained from optimization problems have higher practical significance and value in the real world, it is necessary to develop effective optimization methods under uncertainty. The multi-objective ...

We consider an optimal control problem for a stochastic system whose dynamics is described by a second-order hyperbolic stochastic partial differential equation with Goursat boundary conditions. A stochastic analog of Pontryagin’s maximum principle ...

Data movement is a common performance bottleneck, and its chief remedy is caching. Traditional cache management is transparent to the workload: data that should be kept in cache are determined by the recency information only, while the program information,...

The recovery of used commodities is a major problem for inventory managers due to the limited resources available in the universe. In this paper, it is considered that a retailer sells the new commodity to a purchaser and receives money. The buyer uses ...

Algorithmic game theory is a research field integrating game theory and algorithm design. The major target is to design good algorithms in strategic environments. In this thesis, I intend to study a well-established problem in algorithmic game theory ...

Transforming Dynamic Optimization Problems for Enhanced Computational Efficiency

Dynamic programming is one of the core algorithms for solving optimization problems in operations research, economics, finance, computer science, and numerous other fields. Although the theory itself is relatively straightforward, implementation can be ...

Some approaches to solving challenging dynamic programming problems, such as Q-learning, begin by transforming the Bellman equation into an alternative functional equation to open up a new line of attack. Our paper studies this idea systematically with a ...

We investigate the problem of parameter synthesis for time Petri nets with a cost variable that evolves both continuously with time, and discretely when firing transitions. More precisely, parameters are rational symbolic constants used for time ...

Meta-heuristic algorithms have been proven to be efficient for engineering optimisation. However, the convergence and accuracy of such algorithms depends on the objective function and also on several choices made during algorithm design. In this paper, we ...

In this paper, we resolve several long-standing issues dealing with optimal pointwise in time error bounds for proper orthogonal decomposition (POD) reduced order modeling of the heat equation. In particular, we study the role played by difference ...

The cost of communication is a substantial factor affecting the scalability of many distributed applications. Every message sent can incur a cost in storage, computation, energy, and bandwidth. Consequently, reducing the communication costs of ...

Probabilistic numerics aims to study numerical algorithms from a stochastic perspective. This field has recently evolved into a surging interdisciplinary research area (between numerical approximation and probability theory) attracting much attention from ...

In multiagent blind tournaments, many agents compete at an individual game, unaware of the performance of the other agents. When all agents have completed their games, the agent with the best performance--for example, the highest score, or greatest ...

In this paper, we present several new a posteriori error estimators and two adaptive mixed finite element methods AMFEM1 and AMFEM2 for the Hodge Laplacian problem in finite element exterior calculus. We prove that AMFEM1 and AMFEM2 are both convergent ...

We prove that the a standard adaptive algorithm for the Taylor--Hood discretization of the stationary Stokes problem converges with optimal rate. This is done by developing an abstract framework for quite general problems, which allows us to prove ...

Fixed-priority multicore schedulers are often preferable to dynamic-priority ones because they entail less overhead, are easier to implement, and enable certain tasks to be favored over others. Under global fixed-priority (G-FP) scheduling, as applied ...