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We show how complexity theory can be introduced in machine learning to help bring together apparently disparate areas of current research. We show that this new approach requires less training data and is more generalizable as it shows…

Machine Learning · Computer Science 2019-10-10 Santiago Hernández-Orozco , Hector Zenil , Jürgen Riedel , Adam Uccello , Narsis A. Kiani , Jesper Tegnér

A line of work initiated by Fortnow in 1997 has proven model-independent time-space lower bounds for the $\mathsf{SAT}$ problem and related problems within the polynomial-time hierarchy. For example, for the $\mathsf{SAT}$ problem, the…

Computational Complexity · Computer Science 2021-02-01 Abhijit S. Mudigonda , R. Ryan Williams

This is the full version of a paper submitted to the Computability in Europe (CiE 2023) conference, with all proofs omitted there. In 2012 P. D. Azar and S. Micali introduced a new model of interactive proofs, called "Rational Interactive…

Computational Complexity · Computer Science 2023-05-09 Daniil Musatov , Georgii Potapov

We compare the complexity of the search and decision problems for the complexity class S2P. While Cai (2007) showed that the decision problem is contained in ZPP^NP, we show that the search problem is equivalent to TFNP^NP, the class of…

Computational Complexity · Computer Science 2025-12-03 Lance Fortnow

We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to…

Computer Science and Game Theory · Computer Science 2024-11-12 Xavier Allamigeon , Stéphane Gaubert , Ricardo D. Katz , Mateusz Skomra

The infimal prefix-closed, controllable and observable superlanguage plays an essential role in the relationship between controllability, observability and co-observability -- the central notions of supervisory control theory. Existing…

Systems and Control · Computer Science 2017-03-16 Tomáš Masopust

We explore the computational implications of a superposition of spacetimes, a phenomenon hypothesized in quantum gravity theories. This was initiated by Shmueli (2024) where the author introduced the complexity class $\mathbf{BQP^{OI}}$…

Computational Complexity · Computer Science 2025-04-02 Divesh Aggarwal , Shashwat Agrawal , Rajendra Kumar

In this paper we prove lower bounds on randomized multiparty communication complexity, both in the \emph{blackboard model} (where each message is written on a blackboard for all players to see) and (mainly) in the \emph{message-passing…

Computational Complexity · Computer Science 2015-02-10 Jeff M. Phillips , Elad Verbin , Qin Zhang

We initiate the study of the relationship between two complexity classes, BQP (Bounded-Error Quantum Polynomial-Time) and PPAD (Polynomial Parity Argument, Directed). We first give a conjecture that PPAD is contained in BQP, and show a…

Computational Complexity · Computer Science 2011-08-02 Yang D. Li

We use the powerful tools of counting complexity and generic oracles to help understand the limitations of the complexity of quantum computation. We show several results for the probabilistic quantum class BQP. 1. BQP is low for PP, i.e.,…

Computational Complexity · Computer Science 2007-05-23 Lance Fortnow , John D. Rogers

The main reason for query model's prominence in complexity theory and quantum computing is the presence of concrete lower bounding techniques: polynomial and adversary method. There have been considerable efforts to give lower bounds using…

Quantum Physics · Physics 2024-02-20 Rajat Mittal , Sanjay S Nair , Sunayana Patro

Motivated by certain applications from physics, biochemistry, economics, and computer science, in which the objects under investigation are not accessible because of various limitations, we propose a trial-and-error model to examine…

Computational Complexity · Computer Science 2013-04-19 Xiaohui Bei , Ning Chen , Shengyu Zhang

Many learning problems involve symmetries, and while invariance can be built into neural architectures, it can also emerge implicitly when training on group-structured data. We study this phenomenon in classical Hopfield networks and show…

Machine Learning · Computer Science 2026-01-21 Michael Murray , Tenzin Chan , Kedar Karhadker , Christopher J. Hillar

A graph class admits an implicit representation if, for every positive integer $n$, its $n$-vertex graphs have a $O(\log n)$-bit (adjacency) labeling scheme, i.e., their vertices can be labeled by binary strings of length $O(\log n)$ such…

Combinatorics · Mathematics 2024-09-10 Édouard Bonnet , Julien Duron , John Sylvester , Viktor Zamaraev

The congested clique model of distributed computing has been receiving attention as a model for densely connected distributed systems. While there has been significant progress on the side of upper bounds, we have very little in terms of…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-25 Janne H. Korhonen , Jukka Suomela

As it follows from G\"odel's incompleteness theorems, any consistent formal system of axioms and rules of inference should imply a true unprovable statement. Actually, this fundamental principle can be efficiently applicable in…

Data Structures and Algorithms · Computer Science 2020-11-25 Roman Galay , Daniil Kalistratov

We consider fundamental algorithmic number theoretic problems and their relation to a class of block structured Integer Linear Programs (ILPs) called $2$-stage stochastic. A $2$-stage stochastic ILP is an integer program of the form $\min…

Computational Complexity · Computer Science 2021-02-08 Klaus Jansen , Kim-Manuel Klein , Alexandra Lassota

The complexity of representing a polynomial by a Read-Once Oblivious Algebraic Branching Program (ROABP) is highly dependent on the chosen variable ordering. Bhargava et al. prove that finding the optimal ordering is NP-hard, and provide…

Computational Complexity · Computer Science 2025-09-17 C. Ramya , Pratik Shastri

We address complexity issues for linear differential equations in characteristic $p>0$: resolution and computation of the $p$-curvature. For these tasks, our main focus is on algorithms whose complexity behaves well with respect to $p$. We…

Symbolic Computation · Computer Science 2009-01-27 Alin Bostan , Éric Schost

We study the problem of learning a binary classifier on the vertices of a graph. In particular, we consider classifiers given by monophonic halfspaces, partitions of the vertices that are convex in a certain abstract sense. Monophonic…

Machine Learning · Computer Science 2024-06-19 Marco Bressan , Emmanuel Esposito , Maximilian Thiessen
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