6 citations · 6 across the 4 of their papers we have counts for
6 papers
SLATE: A Sequence Labeling Approach for Task Extraction from Free-form Inked Content
Apurva Gandhi, Ryan Serrao, Biyi Fang +8
We present SLATE, a sequence labeling approach for extracting tasks from free-form content such as digitally handwritten (or "inked") notes on a virtual whiteboard. Our approach al…
Topic Analysis for Text with Side Data
Biyi Fang, Kripa Rajshekhar, Diego Klabjan
Although latent factor models (e.g., matrix factorization) obtain good performance in predictions, they suffer from several problems including cold-start, non-transparency, and sub…
Tricks and Plugins to GBM on Images and Sequences
Biyi Fang, Jean Utke, Diego Klabjan
Convolutional neural networks (CNNs) and transformers, which are composed of multiple processing layers and blocks to learn the representations of data with multiple abstract level…
Neural Network Compression Via Sparse Optimization
Tianyi Chen, Bo Ji, Yixin Shi +4
The compression of deep neural networks (DNNs) to reduce inference cost becomes increasingly important to meet realistic deployment requirements of various applications. There have…
Convergence Analyses of Online ADAM Algorithm in Convex Setting and Two-Layer ReLU Neural Network
Biyi Fang, Diego Klabjan
Nowadays, online learning is an appealing learning paradigm, which is of great interest in practice due to the recent emergence of large scale applications such as online advertisi…
A Stochastic Large-scale Machine Learning Algorithm for Distributed Features and Observations
Biyi Fang, Diego Klabjan
As the size of modern data sets exceeds the disk and memory capacities of a single computer, machine learning practitioners have resorted to parallel and distributed computing. Giv…