15 citations · 47 across the 11 of their papers we have counts for
11 papers
Query lower bounds for log-concave sampling
Sinho Chewi, Jaume de Dios Pont, Jerry Li +2
Log-concave sampling has witnessed remarkable algorithmic advances in recent years, but the corresponding problem of proving lower bounds for this task has remained elusive, with l…
Fisher information lower bounds for sampling
Sinho Chewi, Patrik Gerber, Holden Lee +1
We prove two lower bounds for the complexity of non-log-concave sampling within the framework of Balasubramanian et al. (2022), who introduced the use of Fisher information (FI) bo…
Deep Contrastive Graph Representation via Adaptive Homotopy Learning
Rui Zhang, Chengjun Lu, Ziheng Jiao +1
Homotopy model is an excellent tool exploited by diverse research works in the field of machine learning. However, its flexibility is limited due to lack of adaptiveness, i.e., man…
The query complexity of sampling from strongly log-concave distributions in one dimension
Sinho Chewi, Patrik Gerber, Chen Lu +2
We establish the first tight lower bound of on the query complexity of sampling from the class of strongly log-concave and log-smooth distributions with condition nu…
Rejection sampling from shape-constrained distributions in sublinear time
Sinho Chewi, Patrik Gerber, Chen Lu +2
We consider the task of generating exact samples from a target distribution, known up to normalization, over a finite alphabet. The classical algorithm for this task is rejection s…
Weakly-Supervised Image Semantic Segmentation Using Graph Convolutional Networks
Shun-Yi Pan, Cheng-You Lu, Shih-Po Lee +1
This work addresses weakly-supervised image semantic segmentation based on image-level class labels. One common approach to this task is to propagate the activation scores of Class…