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Related papers: Compact DSOP and partial DSOP Forms

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This paper studies an unsupervised deep learning-based numerical approach for solving partial differential equations (PDEs). The approach makes use of the deep neural network to approximate solutions of PDEs through the compositional…

Machine Learning · Computer Science 2020-08-26 Zhiqiang Cai , Jingshuang Chen , Min Liu , Xinyu Liu

The generating function for $p_N(n)$, the number of partitions of $n$ into at most $N$ parts, may be written as a product of $N$ factors. In part I, we studied the behavior of coefficients in the partial fraction decomposition of this…

Number Theory · Mathematics 2015-07-30 Cormac O'Sullivan

Let $P:\{0,1\}^k \to \{0,1\}$ be a nontrivial $k$-ary predicate. Consider a random instance of the constraint satisfaction problem $\mathrm{CSP}(P)$ on $n$ variables with $\Delta n$ constraints, each being $P$ applied to $k$ randomly chosen…

Computational Complexity · Computer Science 2017-01-18 Pravesh K. Kothari , Ryuhei Mori , Ryan O'Donnell , David Witmer

Dynamic programming (DP) is an algorithmic design paradigm for the efficient, exact solution of otherwise intractable, combinatorial problems. However, DP algorithm design is often presented in an ad-hoc manner. It is sometimes difficult to…

Data Structures and Algorithms · Computer Science 2024-05-17 Max A. Little , Xi He , Ugur Kayas

A weakly infeasible semidefinite program (SDP) has no feasible solution, but it has approximate solutions whose constraint violation is arbitrarily small. These SDPs are ill-posed and numerically often unsolvable. They are also closely…

Optimization and Control · Mathematics 2022-07-11 Gábor Pataki , Aleksandr Touzov

For unweighted graphs, finding isometric embeddings is closely related to decompositions of $G$ into Cartesian products of smaller graphs. When $G$ is isomorphic to a Cartesian graph product, we call the factors of this product a…

Data Structures and Algorithms · Computer Science 2021-12-15 Kristin Sheridan , Joseph Berleant , Mark Bathe , Anne Condon , Virginia Vassilevska Williams

In this paper, we propose a general sparse decomposition of dynamical systems provided that the vector field and constraint set possess certain sparse structures, which we call subsystems. This notion is based on causal dependence in the…

Optimization and Control · Mathematics 2024-08-06 Corbinian Schlosser , Milan Korda

The optimization of chemical processes is challenging due to the nonlinearities arising from process physics and discrete design decisions. In particular, optimal synthesis and design of chemical processes can be posed as a Generalized…

We study the problem of minimizing or maximizing the average value $ f(S)/|S| $ of a submodular or supermodular set function $ f: 2^V \to \mathbb{R} $ over non-empty subsets $ S \subseteq V $. This generalizes classical problems such as…

Data Structures and Algorithms · Computer Science 2025-05-26 Elfarouk Harb , Yousef Yassin , Chandra Chekuri

We show that the formalism of "Sum-Over-Path" (SOP), used for symbolically representing linear maps or quantum operators, together with a proper rewrite system, has a structure of dagger-compact PROP. Several consequences arise from this…

Quantum Physics · Physics 2020-03-13 Renaud Vilmart

Let X be a smooth proper curve over a finite field of characteristic p. We prove a product formula for p-adic epsilon factors of arithmetic D-modules on X. In particular we deduce the analogous formula for overconvergent F-isocrystals,…

Algebraic Geometry · Mathematics 2014-05-14 Tomoyuki Abe , Adriano Marmora

In this paper we study the problem of recovering sparse or compressible signals from uniformly quantized measurements. We present a new class of convex optimization programs, or decoders, coined Basis Pursuit DeQuantizer of moment $p$…

Optimization and Control · Mathematics 2015-03-13 Laurent Jacques , David K. Hammond , M. Jalal Fadili

We propose a method for finding a cumulative distribution function (cdf) that minimizes the distance to a given cdf, while belonging to an ambiguity set constructed relative to another cdf and, possibly, incorporating soft information. Our…

Optimization and Control · Mathematics 2024-08-23 Julio Deride , Johannes O. Royset , Fernanda Urrea

We prove two new results about the randomized query complexity of composed functions. First, we show that the randomized composition conjecture is false: there are families of partial Boolean functions $f$ and $g$ such that $R(f\circ g)\ll…

Computational Complexity · Computer Science 2020-12-08 Shalev Ben-David , Eric Blais

The Sum-of-Squares (SoS) hierarchy of semidefinite programs is a powerful algorithmic paradigm which captures state-of-the-art algorithmic guarantees for a wide array of problems. In the average case setting, SoS lower bounds provide strong…

Computational Complexity · Computer Science 2021-11-18 Chris Jones , Aaron Potechin , Goutham Rajendran , Madhur Tulsiani , Jeff Xu

Functional Principal Component Analysis is a reference method for dimension reduction of curve data. Its theoretical properties are now well understood in the simplified case where the sample curves are fully observed without noise.…

Methodology · Statistics 2025-04-28 Ryad Belhakem , Franck Picard , Vincent Rivoirard , Angelina Roche

The "Subset Sum problem" is a very well-known NP-complete problem. In this work, a top-k variation of the "Subset Sum problem" is considered. This problem has wide application in recommendation systems, where instead of k best objects the k…

Data Structures and Algorithms · Computer Science 2021-08-27 Biswajit Sanyal , Subhashis Majumder , Priya Ranjan Sinha Mahapatra

Given an undirected $n$-vertex graph and $k$ pairs of terminal vertices $(s_1,t_1), \ldots, (s_k,t_k)$, the $k$-Disjoint Shortest Paths ($k$-DSP)-problem asks whether there are $k$ pairwise vertex-disjoint paths $P_1,\ldots, P_k$ such that…

Combinatorics · Mathematics 2022-05-03 Matthias Bentert , André Nichterlein , Malte Renken , Philipp Zschoche

We consider the product of determinantal point processes (DPPs), a point process whose probability mass is proportional to the product of principal minors of multiple matrices, as a natural, promising generalization of DPPs. We study the…

Machine Learning · Computer Science 2021-11-30 Naoto Ohsaka , Tatsuya Matsuoka

In this paper, we propose a new lower approximation scheme for POMDP with discounted and average cost criterion. The approximating functions are determined by their values at a finite number of belief points, and can be computed efficiently…

Artificial Intelligence · Computer Science 2012-07-19 Huizhen Yu , Dimitri Bertsekas
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