Submodular combinatorial information measures with applications in machine learning
Abstract Information-theoretic quantities like entropy and mutual information have found
numerous uses in machine learning. It is well known that there is a strong connection …
numerous uses in machine learning. It is well known that there is a strong connection …
Prophet secretary for combinatorial auctions and matroids
S Ehsani, MT Hajiaghayi, T Kesselheim… - Proceedings of the twenty …, 2018 - SIAM
The secretary and the prophet inequality problems are central to the field of Stopping
Theory. Recently, there has been a lot of work in generalizing these models to multiple items …
Theory. Recently, there has been a lot of work in generalizing these models to multiple items …
Beyond 1/2-approximation for submodular maximization on massive data streams
A Norouzi-Fard, J Tarnawski… - International …, 2018 - proceedings.mlr.press
Many tasks in machine learning and data mining, such as data diversification, non-
parametric learning, kernel machines, clustering etc., require extracting a small but …
parametric learning, kernel machines, clustering etc., require extracting a small but …
Randomized composable core-sets for distributed submodular maximization
V Mirrokni, M Zadimoghaddam - … of the forty-seventh annual ACM …, 2015 - dl.acm.org
An effective technique for solving optimization problems over massive data sets is to
partition the data into smaller pieces, solve the problem on each piece and compute a …
partition the data into smaller pieces, solve the problem on each piece and compute a …
Edge-weighted online bipartite matching
Online bipartite matching is one of the most fundamental problems in the online algorithms
literature. Karp, Vazirani, and Vazirani (STOC 1990) gave an elegant algorithm for …
literature. Karp, Vazirani, and Vazirani (STOC 1990) gave an elegant algorithm for …
Combinatorial prophet inequalities
A Rubinstein, S Singla - Proceedings of the Twenty-Eighth Annual ACM-SIAM …, 2017 - SIAM
We introduce a novel framework of Prophet Inequalities for combinatorial valuation
functions. For a (n on-monotone) submodular objective function over an arbitrary matroid …
functions. For a (n on-monotone) submodular objective function over an arbitrary matroid …
Robust online correlation clustering
In correlation clustering we are given a set of points along with recommendations whether
each pair of points should be placed in the same cluster or into separate clusters. The goal …
each pair of points should be placed in the same cluster or into separate clusters. The goal …
Online edge coloring algorithms via the nibble method
Nearly thirty years ago, Bar-Noy, Motwani and Naor [IPL'92] conjectured that an online (1+ o
(1)) Δ-edge-coloring algorithm exists for n-node graphs of maximum degree Δ= ω (log n) …
(1)) Δ-edge-coloring algorithm exists for n-node graphs of maximum degree Δ= ω (log n) …
Streaming submodular matching meets the primal-dual method
We study streaming submodular maximization subject to matching/b-matching constraints
(MSM/MSbM), and present improved upper and lower bounds for these problems. On the …
(MSM/MSbM), and present improved upper and lower bounds for these problems. On the …
The limitations of optimization from samples
In this paper we consider the following question: can we optimize objective functions from
the training data we use to learn them? We formalize this question through a novel …
the training data we use to learn them? We formalize this question through a novel …