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Poster
Fri 16:30 The Feature Speed Formula: a flexible approach to scale hyper-parameters of deep neural networks
Lénaïc Chizat · Praneeth Netrapalli
Poster
Fri 11:00 Learning to Shape In-distribution Feature Space for Out-of-distribution Detection
Yonggang Zhang · Jie Lu · Bo Peng · Zhen Fang · Yiu-ming Cheung
Workshop
Emergence in non-neural models: grokking modular arithmetic via average gradient outer product
Neil Mallinar · Daniel Beaglehole · Libin Zhu · Adityanarayanan Radhakrishnan · Parthe Pandit · Misha Belkin
Workshop
TabGraphs: A Benchmark and Strong Baselines for Learning on Graphs with Tabular Node Features
Gleb Bazhenov · Oleg Platonov · Liudmila Prokhorenkova
Poster
Fri 11:00 Understanding Visual Feature Reliance through the Lens of Complexity
Thomas Fel · Louis Béthune · Andrew Lampinen · Thomas Serre · Katherine Hermann
Poster
Thu 11:00 Learning Transferable Features for Implicit Neural Representations
Kushal Kardam Vyas · Imtiaz Humayun · Aniket Dashpute · Richard Baraniuk · Ashok Veeraraghavan · Guha Balakrishnan
Poster
Wed 11:00 Infinite-Dimensional Feature Interaction
Chenhui Xu · FUXUN YU · Maoliang Li · Zihao Zheng · Zirui Xu · Jinjun Xiong · Xiang Chen
Poster
Wed 11:00 Learning from Offline Foundation Features with Tensor Augmentations
Emir Konuk · Christos Matsoukas · Moein Sorkhei · Phitchapha Lertsiravarameth · Kevin Smith
Poster
Thu 11:00 Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing
Yixin Ren · Yewei Xia · Hao Zhang · Jihong Guan · Shuigeng Zhou
Poster
Wed 16:30 Differential Privacy in Scalable General Kernel Learning via K-means Nystr{\"o}m Random Features
Bonwoo Lee · Jeongyoun Ahn · Cheolwoo Park
Poster
Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept Drift
Junbao Chen · Jingfeng Xue · Yong Wang · Zhenyan Liu · Lu Huang
Workshop
BoostMD: Accelerated Molecular Sampling Leveraging ML Force Field Features
Lars L Schaaf · Ilyes Batatia · Jules Tilly · Tom Barrett