Tim Hoheisel

30 papers A* 2A 1Journal 27
YearRankTypeTitle / Venue / Authors
2026 J jnl
Data-Driven Priors in the Maximum Entropy on the Mean Method for Linear Inverse Problems.
SIAM J. Math. Data Sci.
Matthew King-Roskamp, Rustum Choksi, Tim Hoheisel
2025 A* conf
Discrete and Continuous Difference of Submodular Minimization.
ICML
George Orfanides, Tim Hoheisel, Marwa El Halabi
2025 J jnl
Discrete and Continuous Difference of Submodular Minimization.
CoRR
George Orfanides, Tim Hoheisel, Marwa El Halabi
2025 J jnl
Maximum entropy on the mean and the Cramér rate function in statistical estimation and inverse problems: properties, models, and algorithms.
Math. Program.
Yakov Vaisbourd, Rustum Choksi, Ariel Goodwin, Tim Hoheisel, Carola-Bibiane Schönlieb
2024 J jnl
Data-Driven Priors in the Maximum Entropy on the Mean Method for Linear Inverse Problems.
CoRR
Matthew King-Roskamp, Rustum Choksi, Tim Hoheisel
2024 J jnl
Square Root LASSO: Well-Posedness, Lipschitz Stability, and the Tuning Trade-Off.
SIAM J. Optim.
Aaron Berk, Simone Brugiapaglia, Tim Hoheisel
2023 J jnl
Difference of Submodular Minimization via DC Programming.
CoRR
Marwa El Halabi, George Orfanides, Tim Hoheisel
2023 A* conf
Difference of submodular minimization via DC programming.
ICML
Marwa El Halabi, George Orfanides, Tim Hoheisel
2023 J jnl
From Perspective Maps to Epigraphical Projections.
Math. Oper. Res.
Michael P. Friedlander, Ariel Goodwin, Tim Hoheisel
2023 J jnl
LASSO Reloaded: A Variational Analysis Perspective with Applications to Compressed Sensing.
SIAM J. Math. Data Sci.
Aaron Berk, Simone Brugiapaglia, Tim Hoheisel
2023 J jnl
Uniqueness in Nuclear Norm Minimization: Flatness of the Nuclear Norm Sphere and Simultaneous Polarization.
J. Optim. Theory Appl.
Tim Hoheisel, Elliot Paquette
2022 J jnl
A study of one-parameter regularization methods for mathematical programs with vanishing constraints.
Optim. Methods Softw.
Tim Hoheisel, Blanca Pablos, Aram-Alexandre Pooladian, Alexandra Schwartz, Luke Steverango
2022 J jnl
LASSO reloaded: a variational analysis perspective with applications to compressed sensing.
CoRR
Aaron Berk, Simone Brugiapaglia, Tim Hoheisel
2022 J jnl
Maximum Entropy on the Mean and the Cramér Rate Function in Statistical Estimation and Inverse Problems: Properties, Models, and Algorithms.
CoRR
Yakov Vaisbourd, Rustum Choksi, Ariel Goodwin, Tim Hoheisel, Carola-Bibiane Schönlieb
2021 J jnl
A Study of Convex Convex-Composite Functions via Infimal Convolution with Applications.
Math. Oper. Res.
James V. Burke, Tim Hoheisel, Quang V. Nguyen
2021 J jnl
Blind Deblurring of Barcodes via Kullback-Leibler Divergence.
IEEE Trans. Pattern Anal. Mach. Intell.
Gabriel Rioux, Christopher Scarvelis, Rustum Choksi, Tim Hoheisel, Pierre Maréchal
2021 J jnl
From perspective maps to epigraphical projections.
CoRR
Michael P. Friedlander, Ariel Goodwin, Tim Hoheisel
2020 A conf
A principled approach for generating adversarial images under non-smooth dissimilarity metrics.
AISTATS
Aram-Alexandre Pooladian, Chris Finlay, Tim Hoheisel, Adam M. Oberman
2020 J jnl
Maximum Entropy on the Mean: A Paradigm Shift for Regularization in Image Deblurring.
CoRR
Gabriel Rioux, Rustum Choksi, Tim Hoheisel, Christopher Scarvelis
2019 J jnl
A principled approach for generating adversarial images under non-smooth dissimilarity metrics.
CoRR
Aram-Alexandre Pooladian, Chris Finlay, Tim Hoheisel, Adam M. Oberman
2019 J jnl
Variational Properties of Matrix Functions via the Generalized Matrix-Fractional Function.
SIAM J. Optim.
James V. Burke, Yuan Gao, Tim Hoheisel
2018 J jnl
Convex Geometry of the Generalized Matrix-Fractional Function.
SIAM J. Optim.
James V. Burke, Yuan Gao, Tim Hoheisel
2017 J jnl
Convex Geometry of the Generalized Matrix-Fractional Function.
CoRR
James V. Burke, Yuan Gao, Tim Hoheisel
2015 J jnl
Matrix Support Functionals for Inverse Problems, Regularization, and Learning.
SIAM J. Optim.
James V. Burke, Tim Hoheisel
2015 J jnl
On a Smooth Dual Gap Function for a Class of Player Convex Generalized Nash Equilibrium Problems.
J. Optim. Theory Appl.
Nadja Harms, Tim Hoheisel, Christian Kanzow
2014 J jnl
On a Smooth Dual Gap Function for a Class of Quasi-Variational Inequalities.
J. Optim. Theory Appl.
Nadja Harms, Tim Hoheisel, Christian Kanzow
2013 J jnl
A smoothing-regularization approach to mathematical programs with vanishing constraints.
Comput. Optim. Appl.
Wolfgang Achtziger, Tim Hoheisel, Christian Kanzow
2013 J jnl
Epi-convergent Smoothing with Applications to Convex Composite Functions.
SIAM J. Optim.
James V. Burke, Tim Hoheisel
2013 J jnl
Theoretical and numerical comparison of relaxation methods for mathematical programs with complementarity constraints.
Math. Program.
Tim Hoheisel, Christian Kanzow, Alexandra Schwartz
2012 J jnl
Convergence of a local regularization approach for mathematical programmes with complementarity or vanishing constraints.
Optim. Methods Softw.
Tim Hoheisel, Christian Kanzow, Alexandra Schwartz