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The viability of adiabatic quantum computation depends on the slow evolution of the Hamiltonian. The adiabatic switching theorem provides an asymptotic series for error estimates in $1/T$, based on the lowest non-zero derivative of the…

Quantum Physics · Physics 2025-12-25 Thomas D. Cohen , Andrew Li , Hyunwoo Oh , Maneesha Sushama Pradeep

An interesting phenomenon arises: Empirical Risk Minimization (ERM) sometimes outperforms methods specifically designed for out-of-distribution tasks. This motivates an investigation into the reasons behind such behavior beyond algorithmic…

Machine Learning · Computer Science 2026-01-21 Hong Zheng , Fei Teng

The purpose of this erratum is to correct the proof of Theorem A.0.1 in the appendix to our article ``Hadamard spaces with isolated flats'' math.GR/0411232, which was jointly authored by Mohamad Hindawi, Hruska and Kleiner. In that…

Group Theory · Mathematics 2014-11-11 G. Christopher Hruska , Bruce Kleiner

The understanding of adaptive algorithms for SDEs is an open area where many issues related to both convergence and stability (long time behaviour) of algorithms are unresolved. This paper considers a very simple adaptive algorithm, based…

Numerical Analysis · Mathematics 2007-05-23 H. Lamba , J. C. Mattingly , A. M. Stuart

Most investigations devoted to the conditions for adiabatic quantum computing are based on the first-order correction ${\bra{\Psi_{\rm ground}(t)}\dot H(t)\ket{\Psi_{\rm excited}(t)} /\Delta E^2(t)\ll1}$. However, it is demonstrated that…

Quantum Physics · Physics 2009-11-11 Gernot Schaller , Sarah Mostame , Ralf Schützhold

Adam is one of the most influential adaptive stochastic algorithms for training deep neural networks, which has been pointed out to be divergent even in the simple convex setting via a few simple counterexamples. Many attempts, such as…

Machine Learning · Computer Science 2022-08-09 Congliang Chen , Li Shen , Fangyu Zou , Wei Liu

We present a straightforward source-to-source transformation that introduces justifications for user-defined constraints into the CHR programming language. Then a scheme of two rules suffices to allow for logical retraction (deletion,…

Artificial Intelligence · Computer Science 2017-09-12 Thom Fruehwirth

Evolutionary algorithms (EAs) are general-purpose problem solvers that usually perform an unbiased search. This is reasonable and desirable in a black-box scenario. For combinatorial optimization problems, often more knowledge about the…

Neural and Evolutionary Computing · Computer Science 2020-04-23 Vahid Roostapour , Jakob Bossek , Frank Neumann

Given two stochastic equations with different drift terms, under very weak assumptions Liptser and Shiryaev provide the equivalence of the laws of the solutions to these equations by means of Girsanov transform. Their assumptions involve…

Probability · Mathematics 2014-11-17 Benedetta Ferrario

We prove a central limit theorem under diffusive scaling for the displacement of a random walk on ${\mathbb Z}^d$ in stationary and ergodic doubly stochastic random environment, under the $\mathcal{H}_{-1}$-condition imposed on the drift…

Probability · Mathematics 2017-02-23 Gady Kozma , Bálint Tóth

This is an erratum for the publication Bolmont & Mathis 2016 (Celestial Mechanics and Dynamical Astronomy, 126, 275-296, https://doi.org/10.1007/s10569-016-9690-3). There was a small mistake for the spin integration of our code which we…

Earth and Planetary Astrophysics · Physics 2019-02-13 Emeline Bolmont , Stéphane Mathis

Test-time adaptation (TTA) addresses distribution shifts for streaming test data in unsupervised settings. Currently, most TTA methods can only deal with minor shifts and rely heavily on heuristic and empirical studies. To advance TTA under…

Machine Learning · Computer Science 2024-04-09 Shurui Gui , Xiner Li , Shuiwang Ji

Recently, we discovered a mistake in our Letter on phase dynamics in granular d-wave superconductors, which we corrected in an Erratum published last week. This is an expanded version of the Erratum, containing details and supporting…

Superconductivity · Physics 2009-11-10 Yogesh N. Joglekar , A. H. Castro Neto , Alexander V. Balatsky

This erratum remedies errors in the literature pertaining to the stable Adams conjecture. As part of the above corrections, we also identify and fix two errors in section 4 of our recent article on the subject. We thank E. Fridelander for…

Algebraic Topology · Mathematics 2026-02-25 Prasit Bhattacharya , Nitu Kitchloo

Accurate time series forecasting models are often compromised by data drift, where underlying data distributions change over time, leading to significant declines in prediction performance. To address this challenge, this study proposes an…

Systems and Control · Electrical Eng. & Systems 2025-12-30 Nikhil Pawar , Guilherme Vieira Hollweg , Akhtar Hussain , Wencong Su , Van-Hai Bui

We consider the setting of multiscale overdamped Langevin stochastic differential equations, and study the problem of learning the drift function of the homogenized dynamics from continuous-time observations of the multiscale system. We…

Numerical Analysis · Mathematics 2024-11-12 Max Hirsch , Andrea Zanoni

Machine learning and deep learning-based decision making has become part of today's software. The goal of this work is to ensure that machine learning and deep learning-based systems are as trusted as traditional software. Traditional…

The purpose of this erratum is to fill a gap in the proof of the `Composite Braid Theorem' in the manuscript "Studying Links Via Closed Braids IV: Composite Links and Split Links (SLVCB-IV)", Inventiones Math, \{bf 102\} Fasc. 1 (1990),…

Geometric Topology · Mathematics 2009-11-10 Joan S. Birman , William W. Menasco

Consider the problem of learning the drift coefficient of a stochastic differential equation from a sample path. In this paper, we assume that the drift is parametrized by a high dimensional vector. We address the question of how long the…

Information Theory · Computer Science 2011-03-10 José Bento , Morteza Ibrahimi , Andrea Montanari

In the course of Darwinian evolution of a population, punctualism is an important phenomenon whereby long periods of genetic stasis alternate with short periods of rapid evolutionary change. This paper provides a mathematical interpretation…

Probability · Mathematics 2009-03-17 Nicolas Champagnat