29.10.2020, 17:00 Uhr:

• Yaim Cooper (Institute for Advanced Study, Princeton)
• The geometry of the loss function of deep neural networks
• Videobroadcast, registration required, check abstract for details

05.11.2020, 17:00 Uhr:

• Kenji Kawaguchi (MIT)
• to be announced
• Videobroadcast, registration required, check abstract for details

12.11.2020, 17:00 Uhr:

• Yasaman Bahri (Google Brain)
• to be announced
• Videobroadcast, registration required, check abstract for details

03.12.2020, 17:00 Uhr:

• Suriya Gunasekar (Microsoft US)
• to be announced
• Videobroadcast, registration required, check abstract for details

02.04.2020, 11:00 Uhr:

• Yu Guang Wang (University of New South Wales, Sydney)
• Haar Graph Pooling
• see PDF Abstract
• see video

09.04.2020, 17:00 Uhr:

• Michael Arbel (University College London)
• Kernelized Wasserstein Natural Gradient
• see video

16.04.2020, 17:00 Uhr:

• Anton Mallasto (University of Copenhagen)
• Estimation of Optimal Transport in Generative Models
• see video

23.04.2020, 17:00 Uhr:

• Johannes Mueller (MPI MIS, Leipzig)
• Deep Ritz Revisited
• see video

30.04.2020, 17:00 Uhr:

• Quynh Nguyen (University Saarbruecken)
• Loss surface of deep and wide neural networks
• see video

07.05.2020, 17:00 Uhr:

• Kathlén Kohn (KTH Royal Institute of Technology)
• The geometry of neural networks
• see video

14.05.2020, 17:00 Uhr:

• Benjamin Fehrman (University of Oxford)
• Convergence rates for the stochastic gradient descent method for non-convex objective functions
• see video

21.05.2020, 17:00 Uhr:

• Dennis Elbrächter (Universität Wien)
• How degenerate is the parametrization of (ReLU) neural networks?
• see video

28.05.2020, 17:00 Uhr:

• Jonathan Frankle (Massachusetts Institute of Technology)
• The Lottery Ticket Hypothesis: On Sparse, Trainable Neural Networks

04.06.2020, 17:00 Uhr:

• Ulrich Terstiege (Rheinisch-Westfälische Technische Hochschule Aachen)
• Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers

11.06.2020, 17:00 Uhr:

• Poorya Mianjy (Johns Hopkins University)
• Understanding the Algorithmic Regularization due to Dropout
• see video

18.06.2020, 17:00 Uhr:

• Alessandro Achille (University of California, Los Angeles)
• Structure of Learning Tasks and the Information in the Weights of a Deep Network
• see video

25.06.2020, 17:00 Uhr:

• Adam Gaier (INRIA)
• Weight Agnostic Neural Networks

02.07.2020, 17:00 Uhr:

• Wenda Zhou (Columbia University)
• New perspectives on cross-validation
• see video

03.07.2020, 17:00 Uhr:

• Kai Fong Ernest Chong (Singapore University of Technology and Design)
• The approximation capabilities of neural networks
• see video

10.07.2020, 17:00 Uhr:

• Nasim Rahaman (MPI-IS Tübingen, and Mila, Montréal)
• On the Spectral Bias of Neural Networks
• see video

23.07.2020, 17:00 Uhr:

• Léonard Blier (Facebook AI Research, Université Paris Saclay, Inria)
• The Description Length of Deep Learning Models

30.07.2020, 17:00 Uhr:

• Robert Peharz (TU Eindhoven)
• Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters
• see video

31.07.2020, 17:00 Uhr:

• Greg Ongie (University of Chicago)
• A function space view of overparameterized neural networks
• see video

06.08.2020, 17:00 Uhr:

• Simon S. Du (University of Washington)
• Ultra-wide Neural Network and Neural Tangent Kernel
• see video

13.08.2020, 17:00 Uhr:

• Lénaïc Chizat (CNRS - Laboratoire de Mathématiques d'Orsay)
• Analysis of Gradient Descent on Wide Two-Layer ReLU Neural Networks
• see video

14.08.2020, 17:00 Uhr:

• Ido Nachum (École Polytechnique Fédérale de Lausanne)
• Regularization by Misclassification in ReLU Neural Networks
• see video

20.08.2020, 17:00 Uhr:

• Arthur Jacot (École Polytechnique Fédérale de Lausanne)
• Neural Tangent Kernel: Convergence and Generalization of DNNs
• see video

21.08.2020, 17:00 Uhr:

• Preetum Nakkiran (Harvard University)
• Distributional Generalization: A New Kind of Generalization
• see video

27.08.2020, 17:00 Uhr:

• Felix Draxler (Heidelberg University)
• Characterizing The Role of A Single Coupling Layer in Affine Normalizing Flows
• see video

03.09.2020, 17:00 Uhr:

• Niladri S. Chatterji (UC Berkeley)
• Upper and lower bounds for gradient based sampling methods
• see video

04.09.2020, 17:00 Uhr:

• Nadav Cohen (Tel Aviv University)
• Analyzing Optimization and Generalization in Deep Learning via Dynamics of Gradient Descent
• see video

17.09.2020, 17:00 Uhr:

• Mahito Sugiyama (National Institute of Informatics, JST, PRESTO)
• Learning with Dually Flat Structure and Incidence Algebra

18.09.2020, 17:00 Uhr:

• Mert Pilanci (Stanford University)
• Exact Polynomial-time Convex Formulations for Training Multilayer Neural Networks: The Hidden Convex Optimization Landscape

24.09.2020, 17:00 Uhr:

• Liwen Zhang (University of Chicago)
• Tropical Geometry of Deep Neural Networks
• see video

25.09.2020, 17:00 Uhr:

• Randall Balestriero (Rice University)
• Max-Affine Spline Insights into Deep Networks
• see video

01.10.2020, 17:00 Uhr:

• David Rolnick (McGill University & Mila)
• Expressivity and learnability: linear regions in deep ReLU networks
• see video

08.10.2020, 17:00 Uhr:

• Yaoyu Zhang (Shanghai Jiao Tong University)
• Impact of initialization on generalization of deep neural networks
• see video

15.10.2020, 17:00 Uhr:

• Guy Blanc (Stanford University)
• Provable Guarantees for Decision Tree Induction

22.10.2020, 17:00 Uhr:

• Boris Hanin (Princeton University)
• Neural Networks at Finite Width and Large Depth