A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Filters
Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness
[article]
2021
arXiv
pre-print
Preserved Fulltext
Other Versions
We investigate the HSIC (Hilbert-Schmidt independence criterion) bottleneck as a regularizer for learning an adversarially robust deep neural network classifier. ...
We show that the HSIC bottleneck enhances robustness to adversarial attacks both theoretically and experimentally. ...
We revisit the HSIC bottleneck, studying its adversarial robustness properties. In contrast to both Alemi et al. [1] and Ma et al. ...
arXiv:2106.02734v2
fatcat:q4b45ttwljhzxg45qgfpnr3j7i
Stronger and Faster Wasserstein Adversarial Attacks
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Furthermore, employing our stronger attacks in adversarial training significantly improves the robustness of adversarially trained models. ...
measuring image quality and has recently risen as a compelling alternative to the ℓ_p metric in adversarial attacks. ...
Semidef-
inite relaxations for certifying robustness to adversarial
examples. In Advances in Neural Information Processing
Systems 31, pp. 10877-10887, 2018.
Rubner, Y., Guibas, L. ...
arXiv:2008.02883v1
fatcat:xeu7cw3ctrfopit2dgw662gqe4
Learning Disentangled Representations in the Imaging Domain
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In this tutorial paper, we motivate the need for disentangled representations, revisit key concepts, and describe practical building blocks and criteria for learning such representations. ...
This alleviation of the data and annotation requirements offers tantalising prospects for applications in computer vision and healthcare. ...
We thank the participants of the DREAM tutorials for feedback. ...
arXiv:2108.12043v5
fatcat:cbpmp6pbajhjvjzovulswuj2wy
Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In this paper, we propose an online model-based RL algorithm, namely the CME-RL, that learns representations of transition distributions as embeddings in a reproducing kernel Hilbert space while carefully ...
However, the understanding of function approximation schemes for state-value functions largely remains missing. ...
However, observe that for any operator M ∈ L(H ϕ , H ψ ) we have M tr(M ⊤ M), where the latter corresponds to the Hilbert-Schmidt norm. ...
arXiv:2011.07881v3
fatcat:qvedjipt4ndlvlq4fe5rzdcoqq
Solving inverse problems using data-driven models
2019
Acta Numerica
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Recent research in inverse problems seeks to develop a mathematically coherent foundation for combining data-driven models, and in particular those based on deep learning, with domain-specific knowledge ...
The authors are moreover grateful to the following people for proofreading the manuscript and providing valuable feedback on its content ...
Clearly, theory for robustness against adversarial attacks in the context of inverse problems is very much an emerging field. ...
doi:10.1017/s0962492919000059
fatcat:2f7te542wrftphdhurcdnw6dqu
Advances in Quantum Cryptography
2020
Advances in Optics and Photonics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications ...
that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study ...
The CHSH inequality can be expressed in this notation as C, P ≤ 2, where P = P z XY |AB , C = 1 −1 1 −1 −1 1 −1 1 1 −1 −1 1 −1 1 1 −1 and C, P = Tr(C T P ) is the Hilbert-Schmidt inner ...
doi:10.1364/aop.361502
fatcat:7xp7i42fjffpblk6g4fhlpgg6m
The Modern Mathematics of Deep Learning
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
For selected approaches, we describe the main ideas in more detail. ...
eigenvalues of the Hessian (or approximately as the robustness of the minimizer
to adversarial perturbations on the parameter space), see [KMN+ 17]. ...
We will revisit this point in Assumption 1.10 and Definition 1.11. ...
arXiv:2105.04026v1
fatcat:lxnfyzr6qfasneo433inpgseia
Self-Organized Evolutionary Process in Sets of Interdependent Variables near the Midpoint of Phase Transition in K-Satisfiability
[chapter]
2001
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Ackerman, John T Strategic Studies Quarterly: An Air Force-Sponsored Strategic Forum for Military, Government, and Academic Professionals. Volume 2, Number 1 -7 Acuff, Hugh F ...
The requirement for larger memory while building big databases can sometimes make this resource a bottleneck for an information indexing system. ...
Hilbert spaces. ...
doi:10.1007/3-540-45443-8_20
fatcat:ght26tu6avh57kkp54kifofaee
Cross-Covariance Models
[chapter]
2017
Encyclopedia of GIS
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Synonyms Cadaster; Land administration system; Land information system; Land policy; Land registry; Property register; Spatial reference frames ...
Cross-References Indexing, Hilbert R-tree, Spatial Indexing, Multimedia Indexing The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the automated discovery ...
Efficient tools for extracting information from geo-spatial data are crucial to organizations which make decisions based on large spatial datasets, including the National Aeronautics and Space Administration ...
doi:10.1007/978-3-319-17885-1_100240
fatcat:2ojzb7es7rhofinw4abol6dgc4
Abstracts of Working Papers in Economics
2000
Abstracts of Working Papers in Economics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Each PRP's type is its private information about the precision of its own records relating to the site. A strategy for a PRP is a function mapping its type into announced levels of precision. ...
The authors model the problem as an incomplete information, simultaneous-move game between PRP's. ...
Rho is a linear operator on a Hilbert space. X subscript t and epsilon subscript t are Hilbert space valued random variables (the epsilon-subscript-t's are iid). ...
doi:10.1017/s0951007900004915
fatcat:62y3byrmc5ag5czgxtoyqmhhdm
Machine learning approaches for time series problems
2022
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
The first pillar of our scientific contributions comprises novel machine learning solutions for the problem of NILM. ...
These aspects bring out many new challenges when trying to extract useful information from time series data using machine learning methods. ...
Grigorios Tsoumakas for their scientific knowledge, their honest feedback and career advice that they provided. ...
doi:10.26262/heal.auth.ir.340363
fatcat:fqggq54crnaxpmaixk4go7kraa
DISSERTATION SEARCHING OVER ENCRYPTED DATA Submitted by
2017
unpublished
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
, bank account information, social security numbers, data income and more information for more than millions of customers and users. ...
Concerns related to data confidentiality rise uncertainty for users maintaining sensitive information. ...
the Gram-Schmidt process for each query. ...
fatcat:ynmzdc4usnet5o7iwyjdneu6bi
The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
We define a free-energy based criterion for hardness and formally connect it to the well-established notion of low-degree hardness for a broad class of statistical problems, namely all Gaussian additive ...
and provide new low-degree lower bounds for sparse linear regression which seem difficult to prove directly. ...
The authors thank Cris Moore and the Santa Fe Institute for hosting the 2018 "Santa Fe Workshop on Limits to Inference in Networks and Noisy Data," where the initial ideas in this paper were formulated ...
arXiv:2205.09727v1
fatcat:jauznr7cbbap5i66yhomkx24f4
Dagstuhl Reports, Volume 1, Issue 8, August 2011, Complete Issue
[article]
2011
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Data bootstrapping and consensus clustering was used to compute the robustness of branches and identify the most informative SNPs. 2. ...
What are the bottlenecks of open science? ...
Learning vector quantization is a robust prototypebased classification method which, together with the relevance learning strategy, assesses the relative contribution of spectral bands for efficient classification ...
doi:10.4230/dagrep.1.8
fatcat:5hegckr6vrbnfbssydweidcwzy
On incorporating inductive biases into deep neural networks
[article]
2022
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Despite the impressive performance, attention is being drawn towards enhancing the (relatively) weaker areas of deep models such as learning with limited resources, robustness, minimal overhead to realize ...
Lars Petersson, for their continuous support of my Ph.D. research. Without their invaluable knowledge in computer vision, feedback, and guidance, I would not have been able to complete my studies. ...
Robustness against information loss One critical requirement of a 3D object classification model is to be robust against information loss. ...
doi:10.25911/ph29-x543
fatcat:m5rkvjyy65hunkbp56qvgkpgqi
« Previous
Showing results 1 — 15 out of 27 results