Archived News.
- 05/2023: Received Gödel Prize together with Samuel Fiorini, Serge Massar, Hans Raj Tiwary, Ronald de Wolf, and Thomas Rothvoss.
- 05/2023: We are organizing the fifth conference on “Discrete Optimization and Machine Learning” in Aug 2023 at GRIPS in Tokyo.
- 02/2023: We are organizing a Thematic Einstein Semester on “Mathematical Optimization for Machine Learning” within the Math+ Cluster of Excellence. The semester consists of various activities throughout the semester with three workshops, a conference, and a summer school as some of the highlights. We are looking forward to seeing you in Berlin!
- 11/2022: We finished our monograph on Frank-Wolfe methods a.k.a. Conditional Gradients. [arxiv] [webpage] [blog]
- 06/2022: Symposium on Theory of Computing (STOC) Test of Time award (10 years) for “Linear vs. Semidefinite Extended Formulations: Exponential Separation and Strong Lower Bounds”, S. Fiorini, S. Massar, S. Pokutta, H.R. Tiwary, R. de Wolf from 2012.
- 06/2022: 6th RIKEN-IMI-ISM-ZIB-MODAL-NHR Workshop on Advances in Classical and Quantum Algorithms for Optimization and Machine Learning in Japan. [link]
- 06/2022: New ZIB videos available. [youtube channel]. (german only)
- 06/2022: Interview on using AI to combat and mitigate climate change (German) [article] [magazine]
- 10/2021: Math+ Cluster presentation at the Humboldt Forum “Mit Mathematik die Welt verbessern?” (German) [video]
- 10/2021: Our group received a Google Research Award to explore the learning of heuristic schedules in MIP solvers.
- 10/2021: One project funded by the Math+ Research Center.
- 11/2020: Our group received a Google Research Award to support our work on Integer Programming solvers.
- 10/2020: Four projects funded by the Math+ Research Center.
- 10/2020: HTW Berlin enters cooperation with Zuse Institute Berlin. ZIB Press Release, HTW Press Release (German)
- 05/2020: Our Special Priority Program (SPP) proposal ‘Theoretical Foundations of Deep Learning’ was funded by DFG. With an overall budget of EUR 8.5m, this program sets out to significantly boost our fundamental understanding of Deep Learning. The coordination team is Gitta Kutyniok (speaker), Martin Burger, Matthias Hein, Sebastian Pokutta, and Ingo Steinwart. DFG Press Release (German), TUB Press Release (German) SPP Homepage
- 04/2020: Research Campus MODAL enters second funding phase
- 03/2020: Preliminary COVID19 forecast model / version for Berlin
- 03/2020: The third conference on “Discrete Optimization and Machine Learning” is cancelled due to COVID-19.
- 09/2019: We are organizing the third conference on “Discrete Optimization and Machine Learning” in May 2020 at Kyoto University in Kyoto.
- 09/2019: TU Berlin and the Berlin School of Mathematics, with the support of MATH+, are organizing the “Combinatorial Optimization at Work (Co@Work) 2020” summer school on September 14 - 26, 2020 at ZIB in Berlin. Application deadline is: June 14, 2020. Intended audience: master/PhD students, Post-docs.
- 09/2019: Sanjeena Dang, Antoine Deza, Swati Gupta, Paul McNicholas, Masashi Sugiyama, and I are organizing a focus program on Data Science and Optimization in November 2019 at the Fields Institute in Toronto.
- 12/2018: Antoine Deza, Takanori Maehara, and I are editing a special issue on “Machine Learning and Discrete Optimization” in Discrete Optimization. Deadline for submission is May, 30th 2019.
- 04/2019: Shipra Agrawal, Adam Elmachtoub, and I are organizing a track on Industrial Engineering and Operations Research at “Machine Learning in Science and Engineering (MLSE)” in June 2019 at the Georgia Institute of Technology in Atlanta.
- 02/2019: Lew Roberts and I are organizing a “Conference on Emerging and Converging Technologies: The Future World” in June 2019 at the Gordon Institute of Business Science in Johannesburg, South Africa.
- 12/2018: We are organizing the second workshop on “Discrete Optimization and Machine Learning” in July 2019 at the Center for Advanced Intelligence in Tokyo.
- 08/2018: We released our Blended Conditional Gradients code on github.
- Summer 2018: We are organizing a workshop on “Discrete Optimization and Machine Learning” in July 2018 at the Center for Advanced Intelligence in Tokyo.
- Spring 2018: We are organizing the “1st Transatlantic-Transpacific Workshop on Machine Learning and Discrete Optimization” in March 2018.
- Spring 2018: Teaching a special topics course on Machine Learning and Discrete Decisions and a VIP project (with M. Bloch) on Machine Learning in Wireless Communication.
- 05/2017: Georgia Tech has now a Ph.D. Program in Machine Learning.
- 12/2016: Passed the first hurdle of the DARPA SC2 challenge [project page].
- 06/2016: Official launch of Machine Learning @ GT Interdisciplinary Research Center.
- 03/2016: David M. McKenney Family Early Career Professor appointment
- 07/2015: Saving Lives @ Birth 2015 Seed Grant Award Nominee “Low-cost Technology to Assess the Risk of Obstructed Labor in Ethiopia” together with B. Dixon and R. Gleason
- 04/2015: ISYE/George Family Foundation Seed Grant in Predictive Health “Non-invasive Pregnancy Diagnostics for Predicting Obstructed Labor” together with B. Dixon and R. Gleason
- 01/2015: CAREER Award, National Science Foundation, 2015
Archived Talks (select).
- 11/2023: (technical) “Conditional Gradients in Machine Learning”. Keynote at Workshop on Geometry and Machine Learning (Leipzig, Germany). [slides]
- 09/2023: (technical) “The approximate Carathéodory problem and an application to quantum mechanics”. Plenary at 7th Workshop on Future Algorithms and Applications (Berlin, Germany).
- 08/2023: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at ICIAM 2023 (Tokyo, Japan). [slides]
- 08/2023: (technical) “Improved local models and new Bell inequalities via Frank-Wolfe algorithms”. Talk at Conference on Discrete Optimization and Machine Learning (Tokyo, Japan). [slides]
- 07/2023: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at Jon-Shmuel Halfway to Twelfty (Paris, France). [slides]
- 06/2023: (general) “Möglichkeiten und Grenzen künstlicher Intelligenz”. Talk at Lange Nacht der Wissenschaften (Berlin, Germany).
- 05/2023: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at University of Magdeburg MathCoRe Lecture (Magdeburg, Germany). [slides]
- 04/2023: (technical) “Conditional Gradients in Machine Learning”. Talk at Yale Statistics and Data Science Seminar Series (New Haven, CT). [slides]
- 03/2023: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at ICERM Workshop: Combinatorics and Optimization (Providence, RI). [slides] [video]
- 03/2023: (technical) “Structured ML Training via Conditional Gradients”. Talk at Columbia IEOR Seminar Series (New York, NY). [slides]
- 03/2023: (technical) “Conditional Gradients – an overview”. Keynote at 2nd Vienna Workshop on Computational Optimization (Vienna, Austria). [slides]
- 03/2023: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at ADA Lovelace Center: Workshop on Optimization and Machine Learning (Waischenfeld, Germany). [slides]
- 12/2022: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at Fields Workshop on Recent Advances in Optimization (Toronto, Canada). [slides]
- 09/2022: (technical) “Convex integer optimization with Frank-Wolfe methods”. Talk at Advances in Classical and Quantum Algorithms for Optimization and Machine Learning (Tokyo, Japan). [slides]
- 07/2022: (technical) “Structured ML Training via Conditional Gradients”. Plenary at Workshop on Algorithmic Optimization and Data Science (Trier, Germany). [slides]
- 04/2022: (technical) “Conditional Gradients in Machine Learning and Optimization”. Talk at IST ELLIS Seminar Series (Klosterneuburg, Austria). [slides]
- 11/2021: (technical) “Discrete Optimization in Machine Learning - an (informal) overview”. Talk at Oberwolfach Workshop on Combinatorial Optimization (Oberwolfach, Germany). [slides]
- 10/2021: (technical) “Fast algorithms for 1-fair packing (and its dual)”. Talk at HIM Workshop: Continuous approaches to discrete optimization (Bonn, Germany). [slides]
- 09/2021: (technical) “Conditional Gradients - a tour d’horizon”. Talk at AI Campus Berlin Tech Lunch Talk (online). [slides]
- 02/2021: (technical) “Structured ML Training via Conditional Gradients”. Talk at IPAM Deep Learning and Combinatorial Optimization Workshop (online). [slides] [video]
- 11/2020: (technical) “Conditional Gradients: Overview and Recent Advances”. Talk at RWTH Aachen Mathematical Colloquium (online). [slides]
- 11/2020: (general) “AI and-for-with-against Humanity?”. Keynote at Human-centric Artificial Intelligence: 2nd French-German-Japanese Symposium (online). [slides]
- 09/2020: (technical) “Restarting Algorithms: Sometimes there is Free Lunch”. Keynote at CPAIOR 2020 (online). [slides] [video]
- 09/2020: (technical) “Robust ML Training with Conditional Gradients”. Talk at CO@Work 2020 Summer School (online). [slides] [video]
- 05/2020: (technical) “Beyond Worst-case Rates: Data-dependent Rates in Learning and Optimization”. Keynote at MIP 2020 (online). [slides] [video]
- 03/2020: (general) “Künstliche Intelligence im Arbeitsalltag”. Keynote at Künstliche Intelligenz: verständlich @ TH Wildau (Wildau, Germany). [slides]
- 09/2019: (technical) “Smooth Constraint Convex Minimization via Conditional Gradients”. Plenary at 19th French-German-Swiss conference on Optimization (Nice, France). [slides]
- 09/2019: (technical) “Mirror Descent and related methods in Linear and Discrete Optimization”. Talk at Cargese Workshop on Combinatorial Optimization (Cargese, France). [slides]
- 07/2019: (technical) “Locally Accelerated Conditional Gradients”. Talk at Research Institute for Mathematical Sciences Seminar, Kyoto University (Kyoto, Japan). [slides]
- 01/2019: (technical) “Smooth Constraint Convex Minimization via Conditional Gradients”. Plenary at INFORMS Computing Society Conference (Knoxville, TN). [slides]
Archived Teaching.
- WS/2023: Discrete Optimization and Machine Learning (seminar)
- SoSe/2023: Discrete Optimization and Machine Learning (seminar)
- WS/2022: Discrete Optimization and Machine Learning (seminar)
- SoSe/2022: Discrete Optimization and Machine Learning (seminar)
- WS/2021: Discrete Optimization and Machine Learning (seminar)
- SoSe/2021: Discrete Optimization and Machine Learning (seminar)
- WS/2020: Discrete Optimization and Machine Learning (seminar)
- SoSe/2020: Discrete Optimization and Machine Learning (seminar)
- WS/2019: Discrete Optimization and Machine Learning (seminar)
- Spring 2018: Machine Learning and Discrete Decisions (lecture)