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Interest in understanding the interplay between noise and the response of a non-linear device cuts across disciplinary boundaries. It is as relevant for unmasking the dynamics of neurons in noisy environments as it is for designing reliable…

Biological Physics · Physics 2011-05-16 Cameron Sobie , Arif Babul , Rogerio de Sousa

Learning with noisy labels is an important and challenging task for training accurate deep neural networks. Some commonly-used loss functions, such as Cross Entropy (CE), suffer from severe overfitting to noisy labels. Robust loss functions…

Machine Learning · Computer Science 2021-08-03 Xiong Zhou , Xianming Liu , Chenyang Wang , Deming Zhai , Junjun Jiang , Xiangyang Ji

An $n$-bit boolean function is resilient to coalitions of size $q$ if any fixed set of $q$ bits is unlikely to influence the function when the other $n-q$ bits are chosen uniformly. We give explicit constructions of depth-$3$ circuits that…

Computational Complexity · Computer Science 2024-07-01 Peter Ivanov , Emanuele Viola

We develop a new technique for proving concentration inequalities which relate between the variance and influences of Boolean functions. Using this technique, we 1. Settle a conjecture of Talagrand [Tal97] proving that $$\int_{\left\{…

Probability · Mathematics 2020-03-13 Ronen Eldan , Renan Gross

This paper studies least-square regression penalized with partly smooth convex regularizers. This class of functions is very large and versatile allowing to promote solutions conforming to some notion of low-complexity. Indeed, they force…

Optimization and Control · Mathematics 2014-07-01 Samuel Vaiter , Gabriel Peyré , Jalal M. Fadili

We prove a structure theorem for stable functions on amenable groups, which extends the arithmetic regularity lemma for stable subsets of finite groups. Given a group $G$, a function $f\colon G\to [-1,1]$ is called stable if the binary…

Logic · Mathematics 2024-06-18 Gabriel Conant , Anand Pillay

Questions of noise stability play an important role in hardness of approximation in computer science as well as in the theory of voting. In many applications, the goal is to find an optimizer of noise stability among all possible partitions…

Probability · Mathematics 2017-02-17 Anindya De , Elchanan Mossel , Joe Neeman

We examine a hierarchy of equivalence classes of quasi-random properties of Boolean Functions. In particular, we prove an equivalence between a number of properties including balanced influences, spectral discrepancy, local strong…

Combinatorics · Mathematics 2022-09-09 Fan Chung , Nicholas Sieger

The r-th order nonlinearity of a Boolean function is the minimum number of elements that have to be changed in its truth table to arrive at a Boolean function of degree at most r. It is shown that the (suitably normalised) r-th order…

Combinatorics · Mathematics 2013-08-15 Kai-Uwe Schmidt

The interest in "Physically Unclonable Function"-devices has increased rapidly over the last few years, as they have several interesting properties for system security related applications like, for example, the management of cryptographic…

Applications · Statistics 2014-09-30 Benjamin Hackl , Daniel Kurz , Clemens Heuberger , Jürgen Pilz , Martin Deutschmann

In this paper we prove results regarding Boolean functions with small spectral norm (the spectral norm of f is $\|\hat{f}\|_1=\sum_{\alpha}|\hat{f}(\alpha)|$). Specifically, we prove the following results for functions $f:\{0,1\}^n \to…

Computational Complexity · Computer Science 2013-05-23 Amir Shpilka , Avishay Tal , Ben lee Volk

In this paper we derive tight bounds on the expected value of products of {\em low influence} functions defined on correlated probability spaces. The proofs are based on extending Fourier theory to an arbitrary number of correlated…

Probability · Mathematics 2009-06-01 Elchanan Mossel

Recent works explore deep learning's success by examining functions or data with hierarchical structure. To study the learning complexity of functions with hierarchical structure, we study the noise stability of functions with tree…

Probability · Mathematics 2025-09-30 Rupert Li , Elchanan Mossel

We prove a lower bound of $\Omega(n^{1/2 - c})$, for all $c>0$, on the query complexity of (two-sided error) non-adaptive algorithms for testing whether an $n$-variable Boolean function is monotone versus constant-far from monotone. This…

Computational Complexity · Computer Science 2014-12-19 Xi Chen , Anindya De , Rocco A. Servedio , Li-Yang Tan

We study the work fluctuations of a particle, confined to a moving harmonic potential, under the influence of friction and external Poissonian shot noise. The asymmetry of the noise induces an effective nonlinearity in the potential, which…

Statistical Mechanics · Physics 2009-11-13 A. Baule , E. G. D. Cohen

We show examples of total Boolean functions that depend on $n$ variables and have spectral sensitivity $\Theta(\sqrt{\log n})$, which is asymptotically minimal. Our main new function combines the Hamming code with the Boolean address…

Computational Complexity · Computer Science 2025-02-21 Krišjānis Prūsis , Jevgēnijs Vihrovs

We consider the influence of stochastic perturbations on stability of a unique positive equilibrium of a difference equation subject to prediction-based control. These perturbations may be multiplicative $$x_{n+1}=f(x_n)-\left( \alpha +…

Dynamical Systems · Mathematics 2016-06-08 Elena Braverman , Conall Kelly , Alexandra Rodkina

Let $T_{\epsilon}$ be the noise operator acting on functions on the boolean cube $\{0,1\}^n$. Let $f$ be a nonnegative function on $\{0,1\}^n$ and let $q \ge 1$. We upper bound the $\ell_q$ norm of $T_{\epsilon} f$ by the average $\ell_q$…

Information Theory · Computer Science 2019-11-13 Alex Samorodnitsky

The influence of a variable is an important concept in the analysis of Boolean functions. The more general notion of influence of a set of variables on a Boolean function has four separate definitions in the literature. In the present work,…

Information Theory · Computer Science 2023-02-15 Aniruddha Biswas , Palash Sarkar

Bourgain showed that any noise stable Boolean function $f$ can be well-approximated by a junta. In this note we give an exponential sharpening of the parameters of Bourgain's result under the additional assumption that $f$ is a halfspace.

Computational Complexity · Computer Science 2012-03-01 Ilias Diakonikolas , Ragesh Jaiswal , Rocco A. Servedio , Li-Yang Tan , Andrew Wan