413 citations · 3.1k across the 143 of their papers we have counts for
5 papers · 1 filter
Improving Precancerous Case Characterization via Transformer-based Ensemble Learning
Yizhen Zhong, Jiajie Xiao, Thomas Vetterli +5
The application of natural language processing (NLP) to cancer pathology reports has been focused on detecting cancer cases, largely ignoring precancerous cases. Improving the char…
On the Interaction Between Differential Privacy and Gradient Compression in Deep Learning
Jimmy Lin
While differential privacy and gradient compression are separately well-researched topics in machine learning, the study of interaction between these two topics is still relatively…
Few-Shot Non-Parametric Learning with Deep Latent Variable Model
Zhiying Jiang, Yiqin Dai, Ji Xin +2
Most real-world problems that machine learning algorithms are expected to solve face the situation with 1) unknown data distribution; 2) little domain-specific knowledge; and 3) da…
Generalized and Scalable Optimal Sparse Decision Trees
Jimmy Lin, Chudi Zhong, Diane Hu +2
Decision tree optimization is notoriously difficult from a computational perspective but essential for the field of interpretable machine learning. Despite efforts over the past 40…
FLOPs as a Direct Optimization Objective for Learning Sparse Neural Networks
Raphael Tang, Ashutosh Adhikari, Jimmy Lin
There exists a plethora of techniques for inducing structured sparsity in parametric models during the optimization process, with the final goal of resource-efficient inference. Ho…