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This paper makes two proposals for Monte Carlo Softmax Search, which is a recently proposed method that is classified as a selective search like the Monte Carlo Tree Search. The first proposal separately defines the node-selection and…

Artificial Intelligence · Computer Science 2020-09-09 Harukazu Igarashi , Yuichi Morioka , Kazumasa Yamamoto

This letter aims at resolving the issues raised in the recent short communication [1] and answered by [2] by proposing a systematic approximation scheme based on non-mapped shape functions, which both allows to fully exploit the unique…

Numerical Analysis · Computer Science 2011-07-20 Stephane PA Bordas , Sundararajan Natarajan

This paper investigates and extends the computationally attractive nonparametric random coefficients estimator of Fox, Kim, Ryan, and Bajari (2011). We show that their estimator is a special case of the nonnegative LASSO, explaining its…

Econometrics · Economics 2019-09-20 Florian Heiss , Stephan Hetzenecker , Maximilian Osterhaus

We present a sparse multidimensional FFT (sMFFT) randomized algorithm for real positive vectors. The algorithm works in any fixed dimension, requires (O(R log(R) log(N)) ) samples and runs in O( R log^2(R) log(N)) complexity (where N is the…

Data Structures and Algorithms · Computer Science 2016-12-08 Pierre-David Letourneau , Harper Langston , Benoit Meister , Richard Lethin

We present a novel feature matching algorithm that systematically utilizes the geometric properties of features such as position, scale, and orientation, in addition to the conventional descriptor vectors. In challenging scenes with the…

Computer Vision and Pattern Recognition · Computer Science 2017-01-23 Sehyung Lee , Jongwoo Lim , Il Hong Suh

Modeling non-stationary processes, where statistical properties vary across the input domain, is a critical challenge in machine learning; yet most scalable methods rely on a simplifying assumption of stationarity. This forces a difficult…

Machine Learning · Computer Science 2026-02-03 Sawan Kumar , Souvik Chakraborty

This paper proposes and analyzes an iterative minimization formulation for search- ing index-1 saddle points of an energy function. This formulation differs from other eigenvector-following methods by constructing a new objective function…

Numerical Analysis · Mathematics 2014-06-10 Weiguo Gao , Jing Leng , Xiang Zhou

This paper presents in detail the originally developed Quadratic Point Estimate Method (QPEM), aimed at efficiently and accurately computing the first four output moments of probabilistic distributions, using 2n^2+1 sample (or sigma)…

Numerical Analysis · Mathematics 2024-03-21 Minhyeok Ko , Konstantinos G. Papakonstantinou

We propose a novel concept of asymmetric feature maps (AFM), which allows to evaluate multiple kernels between a query and database entries without increasing the memory requirements. To demonstrate the advantages of the AFM method, we…

Computer Vision and Pattern Recognition · Computer Science 2017-04-14 Giorgos Tolias , Ondřej Chum

Compute-and-Forward (C&F) has been proposed as an efficient strategy to reduce the backhaul load for the distributed antenna systems. Finding the optimal coefficients in C&F has commonly been treated as a shortest vector problem (SVP),…

Information Theory · Computer Science 2017-04-18 Qinhui Huang , Alister Burr

Semiparametric accelerated failure time (AFT) models are a useful alternative to Cox proportional hazards models, especially when the assumption of constant hazard ratios is untenable. However, rank-based criteria for fitting AFT models are…

Methodology · Statistics 2022-01-20 Piotr M. Suder , Aaron J. Molstad

Assume that $(X_t)_{t\in\Z}$ is a real valued time series admitting a common marginal density $f$ with respect to Lebesgue's measure. Donoho {\it et al.} (1996) propose a near-minimax method based on thresholding wavelets to estimate $f$ on…

Statistics Theory · Mathematics 2011-03-17 Irène Gannaz , Olivier Wintenberger

In this paper we introduce a new approach for approximately counting in bounded degree systems with higher-order constraints. Our main result is an algorithm to approximately count the number of solutions to a CNF formula $\Phi$ when the…

Data Structures and Algorithms · Computer Science 2017-03-17 Ankur Moitra

In this letter, a fast Fourier transform (FFT)-enhanced low-complexity super-resolution sensing algorithm for near-field source localization with both angle and range estimation is proposed. Most traditional near-field source localization…

Signal Processing · Electrical Eng. & Systems 2024-11-26 Yuxiao Wu , Huizhi Wang , Yong Zeng

Factorization machines (FMs) are a powerful tool for regression and classification in the context of sparse observations, that has been successfully applied to collaborative filtering, especially when side information over users or items is…

Machine Learning · Computer Science 2022-12-21 Jill-Jênn Vie , Tomas Rigaux , Hisashi Kashima

We address the problem of estimating a sparse low-rank matrix from its noisy observation. We propose an objective function consisting of a data-fidelity term and two parameterized non-convex penalty functions. Further, we show how to set…

Optimization and Control · Mathematics 2017-04-13 Ankit Parekh , Ivan W. Selesnick

This paper presents a generalization of the "weighted least-squares" (WLS), named "weighted pairing least-squares" (WPLS), which uses a rectangular weight matrix and is suitable for data alignment problems. Two fast solving methods,…

Mathematical Software · Computer Science 2009-05-29 Pierre Courrieu

This paper proposes a data-adaptive factor model (DAFM), a novel framework for extracting common factors that explain the structures of high-dimensional data. DAFM adopts a composite quantile strategy to adaptively capture the full…

Methodology · Statistics 2025-10-02 Seeun Park , Hee-Seok Oh

We introduce here a rewrite system in the group of unimodular matrices, \emph{i.e.}, matrices with integer entries and with determinant equal to $\pm 1$. We use this rewrite system to precisely characterize the mechanism of the Gaussian…

Data Structures and Algorithms · Computer Science 2007-07-05 Ali Akhavi , Céline Moreira

A Random SubMatrix method (RSM) is proposed to calculate the low-rank decomposition of large-scale matrices with known entry percentage \rho. RSM is very fast as the floating-point operations (flops) required are compared favorably with the…

Numerical Analysis · Computer Science 2015-10-28 Yiguang Liu