Notice
Optimal Convex and Nonconvex Regularizers for a Data Source
- document 1 document 2 document 3
- niveau 1 niveau 2 niveau 3
Descriptif
Regularization is a widespread technique used in statistical estimation problems that helps to capture low dimensional structure in the data and improve signal recovery. For computational and geometric reasons, many regularizers are induced by certain classes of convex bodies, such as polyhedral regularizers in dictionary learning. We propose a generalization of this approach by formulating an optimization problem over the space of star bodies to learn the best regularizer for a given dataset. Through a connection with a dual mixed volume inequality for star bodies, we provide a characterization of the population risk minimizers of this problem and establish strong consistency of the empirical risk minimizers. Based on joint work with Oscar Leong, Yong Sheng Soh, and Venkat Chandrasekaran.
Thème
Dans la même collection
-
Combinatorial maps in high genus
LoufBaptisteCombinatorial maps are a model of discrete geometry: they are surfaces made by gluing polygons along their sides, or equivalently, graphs drawn on surfaces. In this talk, I'll focus on the study of
-
Do there exist expanders with non-negative curvature ?
SalezJustinIn this talk I will briefly recall the framework of local weak limits of finite graphs introduced by I. Benjamini and O. Schramm
-
Tail bounds for detection times in mobile hyperbolic graphs
MitscheDieterMotivated by Krioukov et al.'s model of random hyperbolic graphs for real-world networks, and inspired by the analysis of a dynamic model of graphs in Euclidean space by Peres et al., we introduce a
-
Online matching for the multiclass Stochastic Block Model
SOPRANO LOTONahuelA matching in a graph is a set of edges that do not share endpoints. Developing algorithms that find large matchings is an important problem. An algorithm is said to be online if it has to construct
-
Critical cluster cascades
KirchnerMatthiasWe consider a sequence of Poisson cluster point processes...
-
Point processes on higher rank symmetric spaces and their cost
MellickSamuelCost is a natural invariant associated to group actions and invariant point processes on symmetric spaces (such as Euclidean space and hyperbolic space). Informally, it measures how difficult it is to
-
Parallel server systems in extended heavy traffic
CastielEyalThe standard setting for studying parallel server systems (PSS) at the diffusion scale is based on the heavy traffic condition (HTC)...
-
The Maximal Agreement Subtree problem for random trees
BudzinskiThomasConsider two binary trees whose leaves are labelled from 1 to n.
-
An Improved Lower Bound on the Largest Common Subtree of Random Leaf-Labeled Binary Trees
KhezeliAliIt is known that the size of the largest common subtree...
-
Reversible Markov decision processes
AnantharamVenkatA Markov decision process is called reversible if for every stationary Markov control strategy the resulting Markov chain is reversible.
-
The question of connectedness in the Free Uniform Spanning Forest
TimárÁdám DávidThe uniform measure on the set of all spanning trees of a finite graph is a classical object in probability.
-
Tropical convexity: application to linear programming and mean payoff games
GaubertStéphaneLinear programming, and more generally convex semialgebraic programming, makes sense...
Avec les mêmes intervenants et intervenantes
-
Random Tessellation Forests
O'ReillyElizaRandom forests are a popular class of algorithms used for regression and classification.
Sur le même thème
-
Bruit, erreur, anomalie et incertitude dans les données-PUDD
RossiFabriceLes données collectées sont systématiquement soumises à des perturbations de diverses natures, depuis le bruit de mesure de capteurs jusqu’aux erreurs de saisie.
-
Combinatorial maps in high genus
LoufBaptisteCombinatorial maps are a model of discrete geometry: they are surfaces made by gluing polygons along their sides, or equivalently, graphs drawn on surfaces. In this talk, I'll focus on the study of
-
Do there exist expanders with non-negative curvature ?
SalezJustinIn this talk I will briefly recall the framework of local weak limits of finite graphs introduced by I. Benjamini and O. Schramm
-
Tail bounds for detection times in mobile hyperbolic graphs
MitscheDieterMotivated by Krioukov et al.'s model of random hyperbolic graphs for real-world networks, and inspired by the analysis of a dynamic model of graphs in Euclidean space by Peres et al., we introduce a
-
Sofic entropy of processes on infinite random trees
BordenaveCharlesThis is a joint work with Agnes Backhausz et Balasz Szegedy. We define a natural notion of micro-state entropy...
-
Online matching for the multiclass Stochastic Block Model
SOPRANO LOTONahuelA matching in a graph is a set of edges that do not share endpoints. Developing algorithms that find large matchings is an important problem. An algorithm is said to be online if it has to construct
-
Critical cluster cascades
KirchnerMatthiasWe consider a sequence of Poisson cluster point processes...
-
Point processes on higher rank symmetric spaces and their cost
MellickSamuelCost is a natural invariant associated to group actions and invariant point processes on symmetric spaces (such as Euclidean space and hyperbolic space). Informally, it measures how difficult it is to
-
Parallel server systems in extended heavy traffic
CastielEyalThe standard setting for studying parallel server systems (PSS) at the diffusion scale is based on the heavy traffic condition (HTC)...
-
The Maximal Agreement Subtree problem for random trees
BudzinskiThomasConsider two binary trees whose leaves are labelled from 1 to n.
-
An Improved Lower Bound on the Largest Common Subtree of Random Leaf-Labeled Binary Trees
KhezeliAliIt is known that the size of the largest common subtree...
-
Reversible Markov decision processes
AnantharamVenkatA Markov decision process is called reversible if for every stationary Markov control strategy the resulting Markov chain is reversible.
