Helix: Holistic Optimization for Accelerating Iterative Machine Learning

no code implementations • 14 Dec 2018 • Doris Xin, Stephen Macke, Litian Ma, Jialin Liu, Shuchen Song, Aditya Parameswaran

Machine learning workflow development is a process of trial-and-error: developers iterate on workflows by testing out small modifications until the desired accuracy is achieved.

BIG-bench Machine Learning

Helix: Accelerating Human-in-the-loop Machine Learning

no code implementations • 3 Aug 2018 • Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya Parameswaran

Data application developers and data scientists spend an inordinate amount of time iterating on machine learning (ML) workflows -- by modifying the data pre-processing, model training, and post-processing steps -- via trial-and-error to achieve the desired model performance.

BIG-bench Machine Learning Structured Prediction

Entropy-Based Subword Mining with an Application to Word Embeddings

no code implementations • WS 2018 • Ahmed El-Kishky, Frank Xu, Aston Zhang, Stephen Macke, Jiawei Han

Recent literature has shown a wide variety of benefits to mapping traditional one-hot representations of words and phrases to lower-dimensional real-valued vectors known as word embeddings.

Language Modelling Machine Translation +3