Papers
374 papers found
Spectral Methods for Supervised Topic Models
Yining Wang, Jun Zhu
Top-k Multiclass SVM
Maksim Lapin, Matthias Hein, Bernt Schiele
Spatial Transformer Networks
Max Jaderberg, Karen Simonyan, Andrew Zisserman et al.
Space-Time Local Embeddings
Ke Sun, Jun Wang, Alexandros Kalousis et al.
Sparse Embedded $k$-Means Clustering
Weiwei Liu, Xiaobo Shen, Ivor Tsang
The Numerics of GANs
Lars Mescheder, Sebastian Nowozin, Andreas Geiger
Sparse Approximate Conic Hulls
Greg Van Buskirk, Benjamin Raichel, Nicholas Ruozzi
The Sparse Manifold Transform
Yubei Chen, Dylan Paiton, Bruno Olshausen
Video-to-Video Synthesis
Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu et al.
Learning to Screen
Alon Cohen, Avinatan Hassidim, Haim Kaplan et al.
Dancing to Music
Hsin-Ying Lee, Xiaodong Yang, Ming-Yu Liu et al.
Optimal Sparse Decision Trees
Xiyang Hu, Cynthia Rudin, Margo Seltzer
Ode to an ODE
Krzysztof M Choromanski, Jared Quincy Davis, Valerii Likhosherstov et al.
Top-KAST: Top-K Always Sparse Training
Siddhant Jayakumar, Razvan Pascanu, Jack Rae et al.
On the Representation of Solutions to Elliptic PDEs in Barron Spaces
Ziang Chen, Jianfeng Lu, Yulong Lu
Speech-T: Transducer for Text to Speech and Beyond
Jiawei Chen, Xu Tan, Yichong Leng et al.
Searching the Search Space of Vision Transformer
Minghao Chen, Kan Wu, Bolin Ni et al.
Sparse is Enough in Scaling Transformers
Sebastian Jaszczur, Aakanksha Chowdhery, Afroz Mohiuddin et al.
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification
Yongming Rao, Wenliang Zhao, Benlin Liu et al.
Low-Rank Subspaces in GANs
Jiapeng Zhu, Ruili Feng, Yujun Shen et al.
Fair Sortition Made Transparent
Bailey Flanigan, Gregory Kehne, Ariel D Procaccia
Approximation with CNNs in Sobolev Space: with Applications to Classification
Guohao Shen, Yuling Jiao, Yuanyuan Lin et al.
Tight Bounds for Volumetric Spanners and Applications
Aditya Bhaskara, Sepideh Mahabadi, Ali Vakilian
How to Data in Datathons
Carlos Mougan, Richard Plant, Clare Teng et al.
Balanced Training for Sparse GANs
Yite Wang, Jing Wu, NAIRA HOVAKIMYAN et al.