NeurIPS Debriefing Seminar
This seminar ran from 2016 to 2021. It has currently been paused.
The National NeurIPS debriefing is a yearly seminar (inspired by a similar seminar in Paris), where multiple PhD students and/or senior researchers from anywhere in the Netherlands give short presentations on the paper they found the most interesting at the previous NeurIPS conference. If you are interested in NeurIPS, please consider being one of the presenters.
The format is to have two hours of short talks (15 or 20 minutes, in English). It is not required to have attended NeurIPS, and presenters would usually not present their own papers. Talks can be informal, in a friendly atmosphere, so this is an ideal opportunity for PhD students to gain experience in giving presentations.
Upcoming seminars will be announced on the machine learning Netherlands mailing list.
NeurIPS 2021 Debriefing
March 15, 2022
14h00-16h15
This year’s meeting will be online, via zoom: https://uva-live.zoom.us/j/84087666831
14:00-14:30 | Julia Olkhovskaya (VU) | Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination by Foster, Krishnamurthy |
14:30-15:00 | Ahmad Hammoudeh (University of Mons, ISIA Lab & MAIA artificial intelligence Lab) | On the Frequency Bias of Generative Models by Schwarz, Liao, Geiger |
15:00-15:15 | Break | |
15:15-15:45 | Hidde Fokkema (UvA) | Framing RNN as a kernel method: A neural ODE approach by Fermanian, Marion, Vert, Biau |
Canceled: The talk by Mustafa Celikok (TU Delft) on Bayesian Bellman Operators by Fellows, Hartikainen, Whiteson has been canceled.
NeurIPS 2020 Debriefing
Friday March 5, 2021
14h00-17h00
This year’s meeting will be online, via zoom: https://uva-live.zoom.us/j/89293881695
14:00-14:30 | Mustafa Celikok, TU Delft | A Unifying View of Optimism in Episodic Reinforcement Learning by Gergely Neu, Ciara Pike-Burne |
14:30-15:00 | Alexander Mey, TU Delft | Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes by Yi Tian, Jian Qian, Suvrit Sra |
15:00-15:15 | Break | |
15:15-15:45 | Alexander Ly, CWI | Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree by Peizhong Ju, Xiaojun Lin, Jia Liu |
15:45-16:00 | Peter van der Putten, Leiden University | Creative intermezzo |
16:15-16:45 | Jack Mayo, University of Amsterdam | Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards by Kyungjae Lee, Hongjun Yang, Sungbin Lim, Songhwai Oh |
In addition to the talks, we will also have a creative intermezzo, in which Peter van der Putten (Leiden University) will showcase a creative piece using the GPT3 playground that was part of the digital gallery of the NeurIPS Workshop on Machine Learning for Creativity and Design 2020: Link 1, Link 2.
NeurIPS 2019 Debriefing
Friday February 28, 2020
12h30-15h00
Leiden University, Snellius Building, Niels Bohrweg 1, Leiden
Room 176
List of speakers:
Frans Oliehoek, TU Delft | Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning by Van Seijen, Fatemi, Tavakoli |
Wouter Koolen, CWI | Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions by Farina, Kroer, Sandholm |
Albert Senen-Cerda, TU Eindhoven | q-means: A quantum algorithm for unsupervised machine learning by Kerenidis, Landman, Luongo, Prakash |
Free slot for one more speaker |
NeurIPS 2018 Debriefing
Thursday February 14, 2019 15h00-17h00 Leiden University, Snellius Building, Niels Bohrweg 1, Leiden Room 176
List of speakers:
Rémy Degenne, CWI | Coordinate Descent with Bandit Sampling by Salehi, Thiran, Celis |
Changyong Oh, UvA | Geometrically Coupled Monte Carlo Sampling by Rowland et al. |
Zakaria Mhammedi, Australian National University | Direct Runge-Kutta Discretization Achieves Acceleration by Zhang et al. |
Wouter Koolen, CWI | Acceleration through Optimistic No-Regret Dynamics by Wang and Abernethy |
NIPS 2017 Debriefing
Wednesday February 28, 2018
14h00-16h00
Leiden University, Snellius Building, Niels Bohrweg 1, Leiden
Room 174
Thomas Moerland | Thinking Fast and Slow with Deep Learning and Tree Search by Anthony, Tian, Barber | slides |
Dirk van der Hoeven | Parameter free online learning via model selection by Foster, Kale, Mohri, Sridharan | |
Wouter Koolen | Safe and Nested Subgame Solving for Imperfect-Information Games by Brown, Sandholm | |
William Weimin Yoo | Dynamic Routing Between Capsules by Sabour, Frosst, Hinton | slides |
Tim van Erven | A high-level overview of recent thinking on why neural networks generalize, based on:
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slides |
NIPS 2016 Debriefing
Friday January 20, 2017
15h00-16h30
Leiden University, Snellius Building, Niels Bohrweg 1, Leiden
Room 402
List of speakers:
Nishant Mehta: On the Recursive Teaching Dimension of VC Classes by Chen^2, Cheng, Tang
Kevin Duisters: Matrix Completion has No Spurious Local Minimum by Ge, Lee, Ma
Dirk van der Hoeven: Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning by Grill, Valko, Munos
Tim van Erven: Deep Learning without Poor Local Minima by Kawaguchi