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In function inversion, we are given a function $f: [N] \mapsto [N]$, and want to prepare some advice of size $S$, such that we can efficiently invert any image in time $T$. This is a well studied problem with profound connections to…

Quantum Physics · Physics 2020-11-24 Kai-Min Chung , Siyao Guo , Qipeng Liu , Luowen Qian

Empirical risk minimization over classes functions that are bounded for some version of the variation norm has a long history, starting with Total Variation Denoising (Rudin et al., 1992), and has been considered by several recent articles,…

Statistics Theory · Mathematics 2019-08-26 Aurélien F. Bibaut , Mark J. van der Laan

We prove the following restricted projection theorem. Let $n\ge 3$ and $\Sigma \subset S^{n}$ be an $(n-1)$-dimensional $C^2$ manifold such that $\Sigma$ has sectional curvature $>1$. Let $Z \subset \mathbb{R}^{n+1}$ be analytic and let $0…

Classical Analysis and ODEs · Mathematics 2023-12-08 Jiayin Liu

Comparator circuits are a natural circuit model for studying bounded fan-out computation whose power sits between nondeterministic branching programs and general circuits. Despite having been studied for nearly three decades, the first…

Computational Complexity · Computer Science 2021-12-01 Bruno P. Cavalar , Zhenjian Lu

We prove a simple, nearly tight lower bound on the approximate degree of the two-level $\mathsf{AND}$-$\mathsf{OR}$ tree using symmetrization arguments. Specifically, we show that $\widetilde{\mathrm{deg}}(\mathsf{AND}_m \circ…

Computational Complexity · Computer Science 2023-03-23 William Kretschmer

Although there exist plentiful theories of empirical risk minimization (ERM) for supervised learning, current theoretical understandings of ERM for a related problem---stochastic convex optimization (SCO), are limited. In this work, we…

Machine Learning · Computer Science 2017-02-08 Lijun Zhang , Tianbao Yang , Rong Jin

We investigated the asymptotics of high-rate constrained quantization errors for a compactly supported probability measure P on Euclidean spaces whose quantizers are confined to a closed set S. The key tool is the metric projection of K…

Metric Geometry · Mathematics 2025-05-19 Chenxing Qian

Recent advances in randomized incremental methods for minimizing $L$-smooth $\mu$-strongly convex finite sums have culminated in tight complexity of $\tilde{O}((n+\sqrt{n L/\mu})\log(1/\epsilon))$ and $O(n+\sqrt{nL/\epsilon})$, where…

Machine Learning · Computer Science 2020-02-11 Yossi Arjevani , Amit Daniely , Stefanie Jegelka , Hongzhou Lin

A major open problem in proof complexity is to demonstrate that random 3-CNFs with a linear number of clauses require super-polynomial size refutations in bounded-depth Frege systems. We take the first step towards addressing this question…

Computational Complexity · Computer Science 2024-09-04 Svyatoslav Gryaznov , Navid Talebanfard

We establish nearly tight bounds on the expected shrinkage of decision lists and DNF formulas under the $p$-random restriction $\mathbf R_p$ for all values of $p \in [0,1]$. For a function $f$ with domain $\{0,1\}^n$, let $\mathrm{DL}(f)$…

Computational Complexity · Computer Science 2020-12-29 Benjamin Rossman

Constructing a Pseudo Random Function (PRF) is a fundamental problem in cryptology. Such a construction, implemented by truncating the last $m$ bits of permutations of $\{0, 1\}^{n}$ was suggested by Hall et al. (1998). They conjectured…

Combinatorics · Mathematics 2021-03-23 Shoni Gilboa , Shay Gueron

Suppose $0 < \alpha \leq n$, $H: \Bbb R^n \to [0,1]$ is a Lebesgue measurable function, and $A_\alpha(H)$ is the infimum of all numbers $C$ for which the inequality $\int_B H(x) dx \leq C R^\alpha$ holds for all balls $B \subset \Bbb R^n$…

Classical Analysis and ODEs · Mathematics 2022-06-14 Bassam Shayya

Let $\mathcal{L}$ be the special Hermite operator on $\mathbb{C}^n$. As a continuation of the recent results in \cite{SG}, we establish new Strichartz estimates for systems of orthonormal functions associated with general flows of the form…

Functional Analysis · Mathematics 2025-11-24 Sunit Ghosh , Jitendriya Swain

We introduce a new technique proving formula size lower bounds based on the linear programming bound originally introduced by Karchmer, Kushilevitz and Nisan [11] and the theory of stable set polytope. We apply it to majority functions and…

Computational Complexity · Computer Science 2009-02-13 Kenya Ueno

In dimension $4$, we show that a nontrivial flat cone cannot be approximated by smooth Ricci shrinkers with bounded scalar curvature and Harnack inequality, under the pointed-Gromov-Hausdorff topology. As applications, we obtain uniform…

Differential Geometry · Mathematics 2017-02-21 Yu Li , Bing Wang

The hypergraph Moore bound is an elegant statement that characterizes the extremal trade-off between the girth - the number of hyperedges in the smallest cycle or even cover (a subhypergraph with all degrees even) and size - the number of…

Combinatorics · Mathematics 2022-07-25 Jun-Ting Hsieh , Pravesh K. Kothari , Sidhanth Mohanty

High-dimensional sparse modeling via regularization provides a powerful tool for analyzing large-scale data sets and obtaining meaningful, interpretable models. The use of nonconvex penalty functions shows advantage in selecting important…

Methodology · Statistics 2016-05-12 Zemin Zheng , Yingying Fan , Jinchi Lv

Let $(M, g, f, \tau)$ be a complete Ricci shrinker satisfying $\textrm{Ric}+\nabla^2f=\frac{g}{2\tau}$ and let $R$ denote its scalar curvature. For a confined function $V$ on $M$, we obtain a lower bound for the lowest eigenvalue of the…

Differential Geometry · Mathematics 2026-05-25 Xu Cheng , Franciele Conrado , Neilha Pinheiro , Detang Zhou

We study the complexity of optimizing highly smooth convex functions. For a positive integer $p$, we want to find an $\epsilon$-approximate minimum of a convex function $f$, given oracle access to the function and its first $p$ derivatives,…

Optimization and Control · Mathematics 2021-12-06 Ankit Garg , Robin Kothari , Praneeth Netrapalli , Suhail Sherif

Using free random varaibles we find an embedding of the operator space $OH$ in the predual of a von Neumann algebra. The properties of this embedding allow us to determined the projection constant of $OH_n$, i.e. there exists a projection…

Operator Algebras · Mathematics 2007-05-23 Marius Junge
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