28 citations · 120 across the 23 of their papers we have counts for
5 papers · 1 filter
On Extending NLP Techniques from the Categorical to the Latent Space: KL Divergence, Zipf's Law, and Similarity Search
Adam Hare, Yu Chen, Yinan Liu +2
Despite the recent successes of deep learning in natural language processing (NLP), there remains widespread usage of and demand for techniques that do not rely on machine learning…
RackSched: A Microsecond-Scale Scheduler for Rack-Scale Computers (Technical Report)
Hang Zhu, Kostis Kaffes, Zixu Chen +4
Low-latency online services have strict Service Level Objectives (SLOs) that require datacenter systems to support high throughput at microsecond-scale tail latency. Dataplane oper…
Rosella: A Self-Driving Distributed Scheduler for Heterogeneous Clusters
Qiong Wu, Zhenming Liu
Large-scale interactive web services and advanced AI applications make sophisticated decisions in real-time, based on executing a massive amount of computation tasks on thousands o…
On Efficient Constructions of Checkpoints
Yu Chen, Zhenming Liu, Bin Ren +1
Efficient construction of checkpoints/snapshots is a critical tool for training and diagnosing deep learning models. In this paper, we propose a lossy compression scheme for checkp…
BATS: A Spectral Biclustering Approach to Single Document Topic Modeling and Segmentation
Qiong Wu, Adam Hare, Sirui Wang +4
Existing topic modeling and text segmentation methodologies generally require large datasets for training, limiting their capabilities when only small collections of text are avail…