Poster session
in
Workshop: 5th Workshop on practical ML for limited/low resource settings (PML4LRS) @ ICLR 2024
Coffee break + Poster session II
Amir Rezaei Balef · Paul Doucet · Dong Wang · Dorina Weichert · David Kappel · Marcella Astrid · Francesco Corti · YUNFAN ZHAO · Olga Saukh · Richard Freinschlag · Moonjung Eo · Andre Kelm · Israel Mason-Williams · SunJae Maeng · Hiroki Naganuma
Smoothness-Adaptive Sharpness-Aware Minimization for Finding Flatter Minima Hiroki Naganuma, Junhyung Lyle Kim, Anastasios Kyrillidis, Ioannis Mitliagkas
Graph Gaussian Processes for Efficient Robust Monte Carlo Tree Search
Dorina Weichert, Samuel Wiest, Sebastian Houben, Paul PloegerPC-LoRA: Progressive Model Compression with Low Rank Adaptation Injoon Hwang, HaeWon Park, Jooyoung Yang, SunJae Maeng, Youngwan Lee
NEURAL NETWORK COMPRESSION: THE FUNCTIONAL PERSPECTIVE
Israel Mason-WilliamsSelect High-Level Features: Efficient Experts from a Hierarchical Classification Network
André Peter Kelm, Niels Hannemann, Bruno Heberle, Lucas Schmidt, Tim Rolff, Christian Wilms, Ehsan Yaghoubi, Simone FrintropLESS: LEARNING TO SELECT A STRUCTURED ARCHITECTURE OVER FILTER PRUNING AND LOW-RANK DECOMPOSITION
Moonjung Eo, Suhyun Kang, Wonjong RheeGNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks
Lisa Schneckenreiter, Richard Freinschlag, Florian Sestak, Johannes Brandstetter, Günter Klambauer, Andreas MayrSubspace-Configurable Networks
Dong Wang, Olga Saukh, Xiaoxi He, Lothar ThieleImplicit Two-Tower Policies YUNFAN ZHAO, Alvin Pan, Krzysztof Marcin Choromanski, Deepali Jain, Vikas Sindhwani
HADS: Hardware-Aware Deep Subnetworks
Francesco Corti, Balz Maag, Joachim Schauer, Ulrich Pferschy, Olga SaukhBetter (pseudo-)labels for semi-supervised instance segmentation
Francois Porcher, camille couprie, Marc Szafraniec, Jakob VerbeekSUPClust: Active Learning at the Boundaries Yuta Ono, Till Aczel, Benjamin Estermann, Roger Wattenhofer
Bridging Diversity and Uncertainty in Active learning with Self-Supervised Pre-Training Paul Doucet, Benjamin Estermann, Till Aczel, Roger Wattenhofer
Constricting Normal Latent Space for Anomaly Detection with Normal-only Training Data
Marcella Astrid, Muhammad Zaigham Zaheer, Seung-Ik LeeA variational framework for local learning with probabilistic latent representations
David Kappel, Khaleelulla Khan Nazeer, Cabrel Teguemne Fokam, Christian Mayr, Anand SubramoneyTowards Bandit-based Optimization for Automated Machine Learning
Amir Rezaei Balef, Claire Vernade, Katharina Eggensperger