Drug Combination for Treatment of Proliferative Diseases

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As it has become easier and cheaper to collect big datasets in the last few decades, designing efficient and low-cost algorithms for these datasets has attracted unprecedented attention. However, in most applications, even storing datasets as acquired has ...

Many physical and chemical reactions are driven by nonadiabatic processes, which imply the breakdown of the celebrated Born-Oppenheimer approximation. To understand these processes, experimentalists employ spectroscopic techniques. However, the obtained re ...

Cross-validation is commonly used to select the recommendation algorithms that will generalize best on yet unknown data. Yet, in many situations the available dataset used for cross-validation is scarce and the selected algorithm might not be the best suit ...

One of the most basic graph problems, All-Pairs Shortest Paths (APSP) is known to be solvable in n^{3-o(1)} time, and it is widely open whether it has an O(n^{3-ε}) time algorithm for ε > 0. To better understand APSP, one often strives to obtain subcubic t ...

Machine intelligence greatly impacts almost all domains of our societies. It is profoundly changing the field of mechanical engineering with new technical possibilities and processes. The education of future engineers also needs to adapt in terms of techni ...

Astrobot swarms are used to capture astronomical signals to generate the map of the observable universe for the purpose of dark energy studies. The convergence of each swarm in the course of its coordination has to surpass a particular threshold to yield a ...

In this paper, we propose a simple global optimisation algorithm inspired by Pareto’s principle. This algorithm samples most of its solutions within prominent search domains and is equipped with a self-adaptive mechanism to control the dynamic tightening o ...

Gait speed as a powerful biomarker of mobility is mostly assessed in controlled environments, e.g. in the clinic. With wearable inertial sensors, gait speed can be estimated in an objective manner. However, most of the previous works have validated the gai ...

Knapsack and Subset Sum are fundamental NP-hard problems in combinatorial optimization. Recently there has been a growing interest in understanding the best possible pseudopolynomial running times for these problems with respect to various parameters. In t ...

Proximal splitting methods are standard tools for nonsmooth optimization. While primal-dual methods have become very popular in the last decade for their flexibility, primal methods may still be preferred for two reasons: acceleration schemes are more effe ...

The task of optimally designing and scheduling energy systems with a high share of renewable energies is complex and computationally demanding. A widespread method for tackling this task is to apply mixed integer linear programming (MILP). Even though the ...

Drug Combination for Treatment of Proliferative Diseases

Chattez avec Graph Search

Sketches, metrics and fast algorithms

Efficient geometric integrators for the linear and nonlinear time-dependent Schrödinger equation

The Imitation Game: Algorithm Selection by Exploiting Black-Box Recommenders

Faster Monotone Min-Plus Product, Range Mode, and Single Source Replacement Paths

Automated Design: A Journey Across Modelling, Optimization, and Education

Learning convergence prediction of astrobots in multi-object spectrographs

Pareto-like sequential sampling heuristic for global optimisation

Toward a remote assessment of walking bout and speed: application in patients with multiple sclerosis

Knapsack and Subset Sum with Small Items

Yapa: Accelerated Proximal Algorithm For Convex Composite Problems

Data reduction for mixed integer linear programming in complex energy systems