Partition of a set | EPFL Graph Search

In mathematics, a partition of a set is a grouping of its elements into non-empty subsets, in such a way that every element is included in exactly one subset. Every equivalence relation on a set defines a partition of this set, and every partition defines an equivalence relation. A set equipped with an equivalence relation or a partition is sometimes called a setoid, typically in type theory and proof theory. Definition and notation A partition of a set X is a set of non-empty subsets of X such that every element x in X is in exactly one of these subsets (i.e., the subsets are nonempty mutually disjoint sets). Equivalently, a family of sets P is a partition of X if and only if all of the following conditions hold: *The family P does not contain the empty set (that is \emptyset \notin P). *The union of the sets in P is equal to X (that is \textstyle\bigcup_{A\in P} A = X). The sets in P are said to exhaust or cover X. See also collectively exh

Subdeterminant Maximization via Nonconvex Relaxations and Anti-Concentration

Javad Ebrahimi Boroojeni, Damian Mateusz Straszak, Nisheeth Vishnoi

Several fundamental problems that arise in optimization and computer science can be cast as follows: Given vectors v(1), ..., v(m) is an element of R-d and a constraint family B subset of 2([m]), find a set S. B that maximizes the squared volume of the simplex spanned by the vectors in S. A motivating example is the ubiquitous data-summarization problem in machine learning and information retrieval where one is given a collection of feature vectors that represent data such as documents or images. The volume of a collection of vectors is used as a measure of their diversity, and partition or matroid constraints over [m] are imposed in order to ensure resource or fairness constraints. Even with a simple cardinality constraint (B = (([m])(r))), the problem becomes NP-hard and has received much attention starting with a result by Khachiyan [1] who gave an r(O(r)) approximation algorithm for this problem. Recently, Nikolov and Singh [2] presented a convex program and showed how it can be used to estimate the value of the most diverse set when there are multiple cardinality constraints (i.e., when B corresponds to a partition matroid). Their proof of the integrality gap of the convex program relied on an inequality by Gurvits [3], and was recently extended to regular matroids [4], [5]. The question of whether these estimation algorithms can be converted into the more useful approximation algorithms - that also output a set - remained open. The main contribution of this paper is to give the first approximation algorithms for both partition and regular matroids. We present novel formulations for the subdeterminant maximization problem for these matroids; this reduces them to the problem of finding a point that maximizes the absolute value of a nonconvex function over a Cartesian product of probability simplices. The technical core of our results is a new anti-concentration inequality for dependent random variables that arise from these functions which allows us to relate the optimal value of these nonconvex functions to their value at a random point. Unlike prior work on the constrained subdeterminant maximization problem, our proofs do not rely on real-stability or convexity and could be of independent interest both in algorithms and complexity where anti-concentration phenomena has recently been deployed.

Ieee2017

Diversity Embedded Space-Time Codes

Suhas Diggavi, Sanket Dusad

Rate and diversity impose a fundamental trade-off in wireless communication. High-rate space-time codes come at a cost of lower reliability (diversity), and high reliability (diversity) implies a lower rate. However, wireless networks need to support applications with very different Quality-of-Service (QoS) requirements, and it is natural to ask what characteristics should be built into the physical layer link in order to accomodate them. In this paper we de- sign high-rate space-time codes that have a high-diversity code embedded within them. This allows a form of communication where the high-rate code opportunistically takes advantage of good channel realizations while the embedded high-diversity code provides guarantees that at least part of the information is received reliably. We provide constructions of linear and non-linear codes for a fixed transmit alphabet constraint. The non-linear constructions are a natural generalization to wireless channels of multilevel codes developed for the AWGN chan- nel that are matched to binary partitions of QAM and PSK constellations. The importance of set-partitioning to code design for the wireless channel is that it provides a mechanism for translating constraints in the binary domain into lower bounds on diversity protection in the complex domain. We investigate the systems implications of embedded diversity codes by examining value to unequal error protection, rate opportunism and packet delay optimiza- tion. These applications demonstrate that diversity-embedded codes have the potential to outperform traditional single-layer codes in moderate SNR regimes.

2008

Subdeterminant Maximization via Nonconvex Relaxations and Anti-Concentration

Javad Ebrahimi Boroojeni, Damian Mateusz Straszak, Nisheeth Vishnoi

Ieee2017