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This paper investigates how the compositional structure of neural networks shapes their optimization landscape and training dynamics. We analyze the gradient flow associated with overparameterized optimization problems, which can be…

Machine Learning · Computer Science 2025-11-14 Arthur Castello Branco de Oliveira , Dhruv Jatkar , Eduardo Sontag

Recent work by Baratin et al. (2021) sheds light on an intriguing pattern that occurs during the training of deep neural networks: some layers align much more with data compared to other layers (where the alignment is defined as the…

Machine Learning · Statistics 2023-04-12 Yizhang Lou , Chris Mingard , Yoonsoo Nam , Soufiane Hayou

One of interesting issues in two-dimensional superconformal field theories is the existence of anomalous modular transformation properties appearing in some non-compact superconformal models, corresponding to the `mock modularity' in…

High Energy Physics - Theory · Physics 2020-05-19 Yuji Sugawara

We show that the homogeneous approximation property and the comparison theorem hold for arbitrary coherent frames. This observation answers some questions about the density of frames that are not covered by the theory of Balan, Casazza,…

Functional Analysis · Mathematics 2010-12-21 Karlheinz Gröchenig

Deep functional maps have recently emerged as a successful paradigm for non-rigid 3D shape correspondence tasks. An essential step in this pipeline consists in learning feature functions that are used as constraints to solve for a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-30 Souhaib Attaiki , Maks Ovsjanikov

When pre-processing observational data via matching, we seek to approximate each unit with maximally similar peers that had an alternative treatment status--essentially replicating a randomized block design. However, as one considers a…

Econometrics · Economics 2019-05-30 Gentry Johnson , Brian Quistorff , Matt Goldman

A notorious problem in mathematics and physics is to create a solvable model for random sequential adsorption of non-overlapping congruent spheres in the $d$-dimensional Euclidean space with $d\geq 2$. Spheres arrive sequentially at…

Probability · Mathematics 2019-01-25 Souvik Dhara , Johan S. H. van Leeuwaarden , Debankur Mukherjee

We comment on a study by Nadykto et al. recently published in this journal. Earlier work from our group has been misrepresented in this study, and we feel that the claims made need to be amended. Also the analysis of Nadykto et al.…

Studies of discrete languages emerging when neural agents communicate to solve a joint task often look for evidence of compositional structure. This stems for the expectation that such a structure would allow languages to be acquired faster…

Computation and Language · Computer Science 2020-04-28 Eugene Kharitonov , Marco Baroni

In order to better understand feature learning in neural networks, we propose a framework for understanding linear models in tangent feature space where the features are allowed to be transformed during training. We consider linear…

Machine Learning · Computer Science 2024-02-22 Daniel LeJeune , Sina Alemohammad

In this work, we present a novel non-rigid shape matching framework based on multi-resolution functional maps with spectral attention. Existing functional map learning methods all rely on the critical choice of the spectral resolution…

Computer Vision and Pattern Recognition · Computer Science 2022-10-13 Lei Li , Nicolas Donati , Maks Ovsjanikov

This is a Reply to the Comment (cond-mat/9812331) by Kravchenko et al. on our earlier work (cond-mat/9812216).

Strongly Correlated Electrons · Physics 2007-05-23 S. Das Sarma , E. H. Hwang

This article describes the geometry of isomorphisms between complements of geometrically irreducible closed curves in the affine plane $\mathbb{A}^2$, over an arbitrary field, which do not extend to an automorphism of $\mathbb{A}^2$. We…

Algebraic Geometry · Mathematics 2019-09-18 Jérémy Blanc , Jean-Philippe Furter , Mattias Hemmig

Deep neural networks have been shown to learn and rely on spurious correlations present in the data that they are trained on. Reliance on such correlations can cause these networks to malfunction when deployed in the real world, where these…

Machine Learning · Computer Science 2025-05-20 Varun Mulchandani , Jung-Eun Kim

In their thought-provoking paper [1], Belkin et al. illustrate and discuss the shape of risk curves in the context of modern high-complexity learners. Given a fixed training sample size $n$, such curves show the risk of a learner as a…

Machine Learning · Computer Science 2022-06-08 Marco Loog , Tom Viering , Alexander Mey , Jesse H. Krijthe , David M. J. Tax

Contradiction retrieval refers to identifying and extracting documents that explicitly disagree with or refute the content of a query, which is important to many downstream applications like fact checking and data cleaning. To retrieve…

Computation and Language · Computer Science 2024-06-18 Haike Xu , Zongyu Lin , Yizhou Sun , Kai-Wei Chang , Piotr Indyk

The purpose of this article is to discuss some aspects of the convergence analysis performed in the paper [Design of momentum fractional LMS for Hammerstein nonlinear system identification with application to electrically stimulated muscle…

Optimization and Control · Mathematics 2021-03-23 Abdul Wahab , Shujaat Khan , Farrukh Zeeshan Khan

Pollet et al have questioned our claim staked in Phys. Rev. Lett. 103, 085701 (2009) that from the location of sharp features in the compressibility in the trap, it is possible to map out the phase boundary between two phases within…

Quantum Gases · Physics 2010-09-28 Qi Zhou , Yasuyuki Kato , Naoki Kawashima , Nandini Trivedi

A new aspect of understanding a Fano absorption spectrum is presented in terms of the complex spectral analysis. The absorption spectrum of an impurity embedded in semi-infinite superlattice is investigated. The boundary condition on the…

Quantum Physics · Physics 2017-12-06 Taku Fukuta , Savannah Garmon , Kazuki Kanki , Ken-ichi Noba , Satoshi Tanaka

Extended objects such as line or surface operators, interfaces or boundaries play an important role in conformal field theory. Here we propose a systematic approach to the relevant conformal blocks which are argued to coincide with the wave…

High Energy Physics - Theory · Physics 2018-11-14 Mikhail Isachenkov , Pedro Liendo , Yannick Linke , Volker Schomerus
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