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An important result in real algebraic geometry is the projection theorem: every projection of a semialgebraic set is again semialgebraic. This theorem and some of its conclusions lie at the basis of many other results, for example the…

Functional Analysis · Mathematics 2017-09-26 Tom Drescher , Tim Netzer , Andreas Thom

We study the integrality gap of convex mixed-integer programs, that is, the difference between the optimal value of such a problem and the optimal value of its continuous relaxation. We study classes of convex sets whose associated…

Optimization and Control · Mathematics 2026-04-20 Burak Kocuk , Diego Moran Ramirez

Finding a point in the intersection of a collection of closed convex sets, that is the convex feasibility problem, represents the main modeling strategy for many computational problems. In this paper we analyze new stochastic reformulations…

Optimization and Control · Mathematics 2018-01-16 Ion Necoara , Peter Richtarik , Andrei Patrascu

Convergence of a projected stochastic gradient algorithm is demonstrated for convex objective functionals with convex constraint sets in Hilbert spaces. In the convex case, the sequence of iterates ${u_n}$ converges weakly to a point in the…

Optimization and Control · Mathematics 2019-10-01 Caroline Geiersbach , Georg Pflug

How much can randomness help computation? Motivated by this general question and by volume computation, one of the few instances where randomness provably helps, we analyze a notion of dispersion and connect it to asymptotic convex…

Computational Complexity · Computer Science 2008-06-17 Luis Rademacher , Santosh Vempala

The classical subset construction for non-deterministic automata can be generalized to other side-effects captured by a monad. The key insight is that both the state space of the determinized automaton and its semantics---languages over an…

Formal Languages and Automata Theory · Computer Science 2019-05-16 Gerco van Heerdt , Joshua Moerman , Matteo Sammartino , Alexandra Silva

We study quasi-convex optimization problems, where only a subset of the constraints can be sampled, and yet one would like a probabilistic guarantee on the obtained solution with respect to the initial (unknown) optimization problem. Even…

Optimization and Control · Mathematics 2021-01-06 Guillaume O. Berger , Raphaël M. Jungers , Zheming Wang

Necessary and sufficient conditions for the exponentiation of finite-dimensional real Lie algebras of linear operators on complete Hausdorff locally convex spaces are obtained, focused on the equicontinuous case - in particular, necessary…

Functional Analysis · Mathematics 2019-11-12 Rodrigo A. H. M. Cabral

This PhD deals with the notion of pseudo algebraically closed (PAC) extensions of fields. It develops a group-theoretic machinery, based on a generalization of embedding problems, to study these extensions. Perhaps the main result is that…

Number Theory · Mathematics 2009-07-17 Lior Bary-Soroker

We study the structure of the set of algebraic curvature operators satisfying a sectional curvature bound under the light of the emerging field of Convex Algebraic Geometry. More precisely, we determine in which dimensions $n$ this convex…

Differential Geometry · Mathematics 2021-05-14 Renato G. Bettiol , Mario Kummer , Ricardo A. E. Mendes

The coalgebraic modelling of alternating automata and of probabilistic automata has long been obstructed by the absence of distributive laws of the powerset monad over itself, respectively of the powerset monad over the finite distribution…

Logic in Computer Science · Computer Science 2020-10-05 Alexandre Goy , Daniela Petrisan

We present a convex approach to probabilistic segmentation and modeling of time series data. Our approach builds upon recent advances in multivariate total variation regularization, and seeks to learn a separate set of parameters for the…

Machine Learning · Statistics 2015-11-17 Matt Wytock , J. Zico Kolter

F. Wehrung has asked: Given a family $\mathcal{C}$ of subsets of a set $\Omega$, under what conditions will there exist a total ordering on $\Omega$ under which every member of $\mathcal{C}$ is convex? <p> Note that if $A$ and $B$ are…

Combinatorics · Mathematics 2020-11-17 George M. Bergman

For a compact space X we consider extending endomorphisms of the algebra C(X) to be endomorphisms of Arens-Hoffman and Cole extensions of C(X). Given a non-linear, monic polynomial p in C(X)[t], with C(X)[t]/pC(X)[t] semi-simple, we show…

Functional Analysis · Mathematics 2007-05-23 J. F. Feinstein , T. J. Oliver

This article shows the existence of a class of closed bounded matrix convex sets which do not have absolute extreme points. The sets we consider are noncommutative sets, $K_X$, formed by taking matrix convex combinations of a single tuple…

Operator Algebras · Mathematics 2022-02-24 Eric Evert

The concept of convex compactness, weaker than the classical notion of compactness, is introduced and discussed. It is shown that a large class of convex subsets of topological vector spaces shares this property and that is can be used in…

Functional Analysis · Mathematics 2010-06-02 Gordan Zitkovic

A finite set can be supplied with a group structure which can then be used to select (classes of) differential calculi on it via the notions of left-, right- and bicovariance. A corresponding framework has been developed by Woronowicz, more…

q-alg · Mathematics 2008-11-26 K. Bresser , A. Dimakis , F. Mueller-Hoissen , A. Sitarz

Tree convex sets refer to a collection of sets such that each set in the collection is a subtree of a tree whose nodes are the elements of these sets. They extend the concept of row convex sets each of which is an interval over a total…

Data Structures and Algorithms · Computer Science 2009-06-03 Yuanlin Zhang , Forrest Sheng Bao

Convex rank tests are partitions of the symmetric group which have desirable geometric properties. The statistical tests defined by such partitions involve counting all permutations in the equivalence classes. Each class consists of the…

Combinatorics · Mathematics 2008-02-17 Jason Morton , Lior Pachter , Anne Shiu , Bernd Sturmfels , Oliver Wienand

The probability simplex is the set of all probability distributions on a finite set and is the most fundamental object in the finite probability theory. In this paper we give a characterization of statistical models on finite sets which are…

Information Theory · Computer Science 2025-10-07 Hiroshi Nagaoka
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