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Distributed Learning of Finite Gaussian Mixtures
Qiong Zhang · Jiahua Chen
Tue 9:00 Private Estimation with Public Data
Alex Bie · Gautam Kamath · Vikrant Singhal
Affinity Workshop
Mixture of Gaussian Processes with Probabilistic Circuits for Multi-Output Regression
Mingye Zhu · Zhongjie Yu · Martin Trapp · Arseny Skryagin · Kristian Kersting
Thu 9:00 Training stochastic stabilized supralinear networks by dynamics-neutral growth
Wayne Soo · Mate Lengyel
Wed 14:00 GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models
Chen Liang · Wenguan Wang · Jiaxu Miao · Yi Yang
Tue 9:00 Pluralistic Image Completion with Gaussian Mixture Models
Xiaobo Xia · Wenhao Yang · Jie Ren · Yewen Li · Yibing Zhan · Bo Han · Tongliang Liu
Tue 14:00 Robust Model Selection and Nearly-Proper Learning for GMMs
Allen Liu · Jerry Li · Ankur Moitra
Wed 14:00 A Fourier Approach to Mixture Learning
Mingda Qiao · Guru Guruganesh · Ankit Rawat · Kumar Avinava Dubey · Manzil Zaheer
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling
Gerard Ben Arous · Reza Gheissari · Aukosh Jagannath
Thu 14:00 Variational inference via Wasserstein gradient flows
Marc Lambert · Sinho Chewi · Francis Bach · Silvère Bonnabel · Philippe Rigollet
Wed 9:00 Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture Models
Yihan Zhang · Nir Weinberger