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We present a framework to train a structured prediction model by performing smoothing on the inference algorithm it builds upon. Smoothing overcomes the non-smoothness inherent to the maximum margin structured prediction objective, and…

Machine Learning · Statistics 2019-02-11 Krishna Pillutla , Vincent Roulet , Sham M. Kakade , Zaid Harchaoui

We consider the semi-parametric estimation of a scale parameter of a one-dimensional Gaussian process with known smoothness. We suggest an estimator based on quadratic variations and on the moment method. We provide asymptotic…

Statistics Theory · Mathematics 2020-01-22 Jean-Marc Azaïs , François Bachoc , Agnès Lagnoux , Thi Mong Ngoc Nguyen

We formulate a new method of performing high-temperature series expansions for the spin-half Heisenberg model or, more generally, for SU($n$) Heisenberg model with arbitrary $n$. The new method is a novel extension of the well-established…

Statistical Mechanics · Physics 2007-05-23 Noboru Fukushima

The designer's preoccupation to reduce the energy needs and get a better thermal quality of ambiances helped in the development of several packages simulating the dynamic behaviour of buildings. This paper shows the adaptation of a method…

Computational Engineering, Finance, and Science · Computer Science 2012-12-26 H. Boyer , J. P. Chabriat , B. Grondin-Perez , C. Tourrand , J. Brau

We consider the 1D Expected Improvement optimization based on Gaussian processes having spectral densities converging to zero faster than exponentially. We give examples of problems where the optimization trajectory is not dense in the…

Optimization and Control · Mathematics 2012-12-18 Dmitry Yarotsky

The system operators usually need to solve large-scale unit commitment problems within limited time frame for computation. This paper provides a pragmatic solution, showing how by learning and predicting the on/off commitment decisions of…

Optimization and Control · Mathematics 2024-03-19 Farzaneh Pourahmadi , Jalal Kazempour

The Guyer-Krumhansl heat equation has numerous important practical applications in both low-temperature and room temperature heat conduction problems. In recent years, it turned out that the Guyer-Krumhansl model can effectively describe…

Analysis of PDEs · Mathematics 2022-07-14 Anderson Ramos , Róbert Kovács , Mirelson Freitas , Almeida Júnior

Gaussian processes offer a flexible kernel method for regression. While Gaussian processes have many useful theoretical properties and have proven practically useful, they suffer from poor scaling in the number of observations. In…

Machine Learning · Statistics 2021-08-26 Nick Terry , Youngjun Choe

Thermally activated processes are key to understanding the dynamics of physical systems. Thermal diffusion of (quasi-)particles for instance not only yields information on transport and dissipation processes but is also an exponentially…

In this paper, we consider a nonsmooth convex finite-sum problem with a conic constraint. To overcome the challenge of projecting onto the constraint set and computing the full (sub)gradient, we introduce a primal-dual incremental gradient…

Optimization and Control · Mathematics 2021-05-10 Afrooz Jalilzadeh

Studying the impact of systematic effects, optimizing survey strategies, assessing tensions between different probes and exploring synergies of different data sets require a large number of simulated likelihood analyses, each of which cost…

Cosmology and Nongalactic Astrophysics · Physics 2022-12-07 Supranta S. Boruah , Tim Eifler , Vivian Miranda , Sai Krishanth P. M

The problem of successfully simulating ionic fluids at low temperature and low density states is well known in the simulation literature: using conventional methods, the system is not able to equilibrate rapidly due to the presence of…

Soft Condensed Matter · Physics 2015-05-14 Chantal Valeriani , Philip J. Camp , Jos W. Zwanikken , René van Roij , Marjolein Dijkstra

We investigate the effect of initial system-environment correlations to improve the estimation of environment parameters. By employing various physical situations of interest, we present results for the environment temperature and…

Quantum Physics · Physics 2024-07-08 Ali Raza Mirza , Jim Al-Khalili

A way to accelerate DEM calculations on the GPUs is developed. We examined how warp divergences take place in the contact detection and the force calculations taking account of the GPU architecture. Then we showed a strategy to reduce the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-13 Yasuhiro Nakahara , Teruyoshi Washizawa

The parabolic-elliptic Keller-Segel equation with sensitivity saturation, because of its pattern formation ability, is a challenge for numerical simulations. We provide two finite-volume schemes whose goals are to preserve, at the discrete…

Numerical Analysis · Mathematics 2018-10-30 Luís Neves de Almeida , Federica Bubba , Benoît Perthame , Camille Pouchol

Interesting problems in quantum computation take the form of finding low-energy states of (pseudo)spin systems with engineered Hamiltonians that encode the problem data. Motivated by the practical possibility of producing very…

Quantum Physics · Physics 2022-05-11 Jiajin Feng , Biao Wu , Frank Wilczek

The dissipative nature of heat transfer relaxes thermal flows to an equilibrium state that is devoid of temperature gradients. The distance to reach an equilibrium temperature -- the thermal entrance length -- is a consequence of diffusion…

Fluid Dynamics · Physics 2021-06-22 S. Beetham , A. Lattanzi , J. Capecelatro

We investigate whether the late-time (at $z\leq 100$) velocity dispersion expected in Warm Dark Matter scenarios could have some effect on the cosmic web (i.e., outside of virialized halos). We consider effective hydrodynamical equations,…

Cosmology and Nongalactic Astrophysics · Physics 2013-05-30 Patrick Valageas

We reconsider a nonparametric density model based on Gaussian processes. By augmenting the model with latent P\'olya--Gamma random variables and a latent marked Poisson process we obtain a new likelihood which is conjugate to the model's…

Machine Learning · Statistics 2018-05-30 Christian Donner , Manfred Opper

We present the first $N$-body simulations that adapt the equations of smoothed particle hydrodynamics to capture the effect of dark matter self-interactions which are too frequent to be resolved explicitly. The relevant energy transfer…

Cosmology and Nongalactic Astrophysics · Physics 2019-10-22 Janis Kummer , Marcus Brüggen , Klaus Dolag , Felix Kahlhoefer , Kai Schmidt-Hoberg
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