Mark Herbster

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 29

Top Topics

Matrix Completion

Convex Optimisation

Top Venues

Publications

Stephen Pasteris, Fabio Vitale, Mark Herbster, Claudio Gentile, André Panisson
Adversarial Online Collaborative Filtering. ALT (2024)
Stephen Pasteris, Alberto Rumi, Maximilian Thiessen, Shota Saito, Atsushi Miyauchi, Fabio Vitale, Mark Herbster
Bandits with Abstention under Expert Advice. CoRR (2024)
Stephen Pasteris, Chris Hicks, Vasilios Mavroudis, Mark Herbster
Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneously. CoRR (2024)
Stephen Pasteris, Fabio Vitale, Mark Herbster, Claudio Gentile
Regret Guarantees for Adversarial Online Collaborative Filtering. CoRR (2023)
Shota Saito, Mark Herbster
Multi-class Graph Clustering via Approximated Effective p-Resistance. CoRR (2023)
Shota Saito, Mark Herbster
Multi-class Graph Clustering via Approximated Effective p-Resistance. ICML (2023)
Shota Saito, Mark Herbster
Generalizing p-Laplacian: spectral hypergraph theory and a partitioning algorithm. Mach. Learn. 112 (1) (2023)
Lin Yang, Yu-Zhen Janice Chen, Mohammad H. Hajiesmaili, Mark Herbster, Don Towsley
Hierarchical Learning Algorithms for Multi-scale Expert Problems. SIGMETRICS (Abstracts) (2022)
Lin Yang, Yu-Zhen Janice Chen, Mohammad H. Hajiesmaili, Mark Herbster, Don Towsley
Hierarchical Learning Algorithms for Multi-scale Expert Problems. Proc. ACM Meas. Anal. Comput. Syst. 6 (2) (2022)
James Robinson, Mark Herbster
Improved Regret Bounds for Tracking Experts with Memory. NeurIPS (2021)
Mark Herbster, Stephen Pasteris, Fabio Vitale, Massimiliano Pontil
A Gang of Adversarial Bandits. NeurIPS (2021)
James Robinson, Mark Herbster
Improved Regret Bounds for Tracking Experts with Memory. CoRR (2021)
Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster
Online Learning of Facility Locations. ALT (2021)
Mark Herbster, Stephen Pasteris, Lisa Tse
Online Multitask Learning with Long-Term Memory. NeurIPS (2020)
Mark Herbster, Stephen Pasteris, Lisa Tse
Online Multitask Learning with Long-Term Memory. CoRR (2020)
Mark Herbster, Stephen Pasteris, Lisa Tse
Online Matrix Completion with Side Information. NeurIPS (2020)
Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster
Online Learning of Facility Locations. CoRR (2020)
Stephen Pasteris, Fabio Vitale, Kevin S. Chan, Shiqiang Wang, Mark Herbster
MaxHedge: Maximizing a Maximum Online. AISTATS (2019)
Stephen Pasteris, Shiqiang Wang, Mark Herbster, Ting He
Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems. CoRR (2019)
Mark Herbster, James Robinson
Online Prediction of Switching Graph Labelings with Cluster Specialists. NeurIPS (2019)
Stephen Pasteris, Shiqiang Wang, Mark Herbster, Ting He
Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems. INFOCOM (2019)
Mark Herbster, Stephen Pasteris, Lisa Tse
Online Matrix Completion with Side Information. CoRR (2019)
Danial Dervovic, Mark Herbster, Peter Mountney, Simone Severini, Naïri Usher, Leonard Wossnig
Quantum linear systems algorithms: a primer. CoRR (2018)
Mark Herbster, James Robinson
Predicting Switching Graph Labelings with Cluster Specialists. CoRR (2018)
Stephen Pasteris, Fabio Vitale, Claudio Gentile, Mark Herbster
On Similarity Prediction and Pairwise Clustering. ALT (2018)
Stephen Pasteris, Fabio Vitale, Claudio Gentile, Mark Herbster
On Pairwise Clustering with Side Information. CoRR (2017)
Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo, Massimiliano Pontil, Andrea Rocchetto, Simone Severini, Leonard Wossnig
Quantum machine learning: a classical perspective. CoRR (2017)
Stephen Pasteris, Shiqiang Wang, Christian Makaya, Kevin Chan, Mark Herbster
Data distribution and scheduling for distributed analytics tasks. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI (2017)
Mark Herbster, Stephen Pasteris, Massimiliano Pontil
Mistake Bounds for Binary Matrix Completion. NIPS (2016)
Mark Herbster, Stephen Pasteris, Shaona Ghosh
Online Prediction at the Limit of Zero Temperature. NIPS (2015)
Mark Herbster, Paul Rubenstein, James Townsend
The VC-Dimension of Similarity Hypotheses Spaces. CoRR (2015)
Mark Herbster, Stephen Pasteris, Massimiliano Pontil
Predicting a switching sequence of graph labelings. J. Mach. Learn. Res. 16 (2015)
Claudio Gentile, Mark Herbster, Stephen Pasteris
Online Similarity Prediction of Networked Data from Known and Unknown Graphs. COLT (2013)
Claudio Gentile, Mark Herbster, Stephen Pasteris
Online Similarity Prediction of Networked Data from Known and Unknown Graphs CoRR (2013)
Mark Herbster, Stephen Pasteris, Fabio Vitale
Online Sum-Product Computation Over Trees. NIPS (2012)
Mark Herbster, Guy Lever
Predicting the Labelling of a Graph via Minimum $p$-Seminorm Interpolation. COLT (2009)
Mark Herbster
Exploiting Cluster-Structure to Predict the Labeling of a Graph. ALT (2008)
Mark Herbster, Massimiliano Pontil, Sergio Rojas Galeano
Fast Prediction on a Tree. NIPS (2008)
Mark Herbster, Guy Lever, Massimiliano Pontil
Online Prediction on Large Diameter Graphs. NIPS (2008)
Mark Herbster, Massimiliano Pontil
Prediction on a Graph with a Perceptron. NIPS (2006)
Mark Herbster, Massimiliano Pontil, Lisa Wainer
Online learning over graphs. ICML (2005)
Andreas Argyriou, Mark Herbster, Massimiliano Pontil
Combining Graph Laplacians for Semi-Supervised Learning. NIPS (2005)
Mark Herbster
Relative Loss Bounds and Polynomial-Time Predictions for the k-lms-net Algorithm. ALT (2004)
Mark Herbster, Manfred K. Warmuth
Tracking the Best Linear Predictor. J. Mach. Learn. Res. 1 (2001)
Mark Herbster
Learning Additive Models Online with Fast Evaluating Kernels. COLT/EuroCOLT (2001)
Mark Herbster, Manfred K. Warmuth
Tracking the Best Regressor. COLT (1998)
Mark Herbster, Manfred K. Warmuth
Tracking the Best Expert. Mach. Learn. 32 (2) (1998)
Peter Auer, Mark Herbster, Manfred K. Warmuth
Exponentially many local minima for single neurons. NIPS (1995)
Mark Herbster, Manfred K. Warmuth
Tracking the Best Expert. ICML (1995)
Leslie Grate, Mark Herbster, Richard Hughey, David Haussler, I. Saira Mian, Harry Noller
RNA Modeling Using Gibbs Sampling and Stochastic Context Free Grammars. ISMB (1994)