English
Related papers

Related papers: Toward Better Depth Lower Bounds: A KRW-like theor…

200 papers

One of the major open problems in complexity theory is proving super-logarithmic lower bounds on the depth of circuits (i.e., $\mathbf{P}\not\subseteq\mathbf{NC}^1$). Karchmer, Raz, and Wigderson (Computational Complexity 5(3/4), 1995)…

Computational Complexity · Computer Science 2025-05-08 Susanna F. de Rezende , Or Meir , Jakob Nordström , Toniann Pitassi , Robert Robere

Proving formula depth lower bounds is a fundamental challenge in complexity theory, with the strongest known bound of $(3 - o(1))\log n$ established by Hastad over 25 years ago. The Karchmer-Raz-Wigderson (KRW) conjecture offers a promising…

Computational Complexity · Computer Science 2025-01-30 Nikolai Chukhin , Alexander S. Kulikov , Ivan Mihajlin

In Direct Sum problems [KRW], one tries to show that for a given computational model, the complexity of computing a collection of finite functions on independent inputs is approximately the sum of their individual complexities. In this…

Computational Complexity · Computer Science 2016-11-17 Andrew Drucker

A direct sum decomposition theory is developed for direct summands (and complements) of modules over a semiring $R$, having the property that $v+w = 0$ implies $v = 0$ and $w = 0$. Although this never occurs when $R$ is a ring, it always…

Rings and Algebras · Mathematics 2015-12-07 Zur Izhakian , Manfred Knebusch , Louis Rowen

Finite-sum optimization plays an important role in the area of machine learning, and hence has triggered a surge of interest in recent years. To address this optimization problem, various randomized incremental gradient methods have been…

Machine Learning · Computer Science 2022-06-22 Min Zhang , Yao Shu , Kun He

A strong direct product theorem states that, in order to solve k instances of a problem, if we provide less than k times the resource required to compute one instance, then the probability of overall success is exponentially small in k. In…

Computational Complexity · Computer Science 2013-02-20 Rahul Jain , Penghui Yao

We prove two new results about the randomized query complexity of composed functions. First, we show that the randomized composition conjecture is false: there are families of partial Boolean functions $f$ and $g$ such that $R(f\circ g)\ll…

Computational Complexity · Computer Science 2020-12-08 Shalev Ben-David , Eric Blais

Cook and Reckhow 1979 pointed out that NP is not closed under complementation iff there is no propositional proof system that admits polynomial size proofs of all tautologies. Theory of proof complexity generators aims at constructing sets…

Computational Complexity · Computer Science 2024-06-12 Jan Krajicek

Let $R_\epsilon(\cdot)$ stand for the bounded-error randomized query complexity with error $\epsilon > 0$. For any relation $f \subseteq \{0,1\}^n \times S$ and partial Boolean function $g \subseteq \{0,1\}^m \times \{0,1\}$, we show that…

Computational Complexity · Computer Science 2018-11-28 Dmitry Gavinsky , Troy Lee , Miklos Santha , Swagato Sanyal

We reduce the problem of proving deterministic and nondeterministic Boolean circuit size lower bounds to the analysis of certain two-dimensional combinatorial cover problems. This is obtained by combining results of Razborov (1989),…

Computational Complexity · Computer Science 2025-03-19 Bruno P. Cavalar , Igor C. Oliveira

We establish two results regarding the query complexity of bounded-error randomized algorithms. * Bounded-error separation theorem. There exists a total function $f : \{0,1\}^n \to \{0,1\}$ whose $\epsilon$-error randomized query complexity…

Computational Complexity · Computer Science 2019-08-06 Eric Blais , Joshua Brody

Depth of an object concerns a tradeoff between computation time and excess of program length over the shortest program length required to obtain the object. It gives an unconditional lower bound on the computation time from a given program…

Computational Complexity · Computer Science 2008-09-16 Luis Antunes , Armando Matos , Andre Souto , Paul Vitanyi

According to Kumar's recent surprising result (ToCT'20), a small border Waring rank implies that the polynomial can be approximated as a sum of a constant and a small product of linear polynomials. We prove the converse of Kumar's result…

Computational Complexity · Computer Science 2025-05-29 Pranjal Dutta , Fulvio Gesmundo , Christian Ikenmeyer , Gorav Jindal , Vladimir Lysikov

We prove a query complexity variant of the weak polynomial Freiman-Ruzsa conjecture in the following form. For any $\epsilon > 0$, a set $A \subset \mathbb{Z}^d$ with doubling $K$ has a subset of size at least $K^{-\frac{4}{\epsilon}}|A|$…

Number Theory · Mathematics 2022-01-14 Dmitrii Zhelezov , Dömötör Pálvölgyi

The subset sum problem is one of the simplest and most fundamental NP-hard problems in combinatorial optimization. We consider two extensions of this problem: The subset sum problem with digraph constraint (SSG) and subset sum problem with…

Discrete Mathematics · Computer Science 2020-06-24 Frank Gurski , Dominique Komander , Carolin Rehs

Modular composition is the problem of computing the coefficient vector of the polynomial $f(g(x)) \bmod h(x)$, given as input the coefficient vectors of univariate polynomials $f$, $g$, and $h$ over an underlying field $\mathbb{F}$. While…

Computational Complexity · Computer Science 2026-01-29 Robert Andrews , Mrinal Kumar , Shanthanu S. Rai

We study the asymptotics and fine-scale behavior of quantitative combinatorial measures of infinite words and related dynamical and algebraic structures. We construct infinite recurrent words $w$ whose complexity functions $p_w(n)$ are…

Combinatorics · Mathematics 2025-08-26 Be'eri Greenfeld , Carlos Gustavo Moreira , Efim Zelmanov

We study the complexity of computing majority as a composition of local functions: \[ \text{Maj}_n = h(g_1,\ldots,g_m), \] where each $g_j :\{0,1\}^{n} \to \{0,1\}$ is an arbitrary function that queries only $k \ll n$ variables and $h :…

Computational Complexity · Computer Science 2022-05-18 Victor Lecomte , Prasanna Ramakrishnan , Li-Yang Tan

It is well understood that different neural network architectures are suited to different tasks, but is there always a single best architecture for a given task? We compare the expressive power of transformers, RNNs, and transformers with…

Machine Learning · Computer Science 2026-01-29 Gilad Yehudai , Noah Amsel , Joan Bruna

In studying the expressiveness of neural networks, an important question is whether there are functions which can only be approximated by sufficiently deep networks, assuming their size is bounded. However, for constant depths, existing…

Machine Learning · Computer Science 2020-12-29 Gal Vardi , Ohad Shamir
‹ Prev 1 2 3 10 Next ›