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05/25/2022
NECA: Network-Embedded Deep Representation Learning for Categorical Data
We propose NECA, a deep representation learning method for categorical d...
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10/16/2021
Metadata Shaping: Natural Language Annotations for the Tail
Language models (LMs) have made remarkable progress, but still struggle ...
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10/15/2021
Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text
Named entity disambiguation (NED), which involves mapping textual mentio...
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10/22/2020
Sharp Bias-variance Tradeoffs of Hard Parameter Sharing in High-dimensional Linear Regression
Hard parameter sharing for multi-task learning is widely used in empiric...
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10/20/2020
Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
A challenge for named entity disambiguation (NED), the task of mapping t...
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06/26/2020
Train and You'll Miss It: Interactive Model Iteration with Weak Supervision and Pre-Trained Embeddings
Our goal is to enable machine learning systems to be trained interactive...
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05/02/2020
Understanding and Improving Information Transfer in Multi-Task Learning
We investigate multi-task learning approaches that use a shared feature ...
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05/02/2020
On the Generalization Effects of Linear Transformations in Data Augmentation
Data augmentation is a powerful technique to improve performance in appl...
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04/11/2020
Ivy: Instrumental Variable Synthesis for Causal Inference
A popular way to estimate the causal effect of a variable x on y from ob...
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02/29/2020
Understanding the Downstream Instability of Word Embeddings
Many industrial machine learning (ML) systems require frequent retrainin...
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09/13/2019
Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices
In real-world machine learning applications, data subsets correspond to ...
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11/28/2017
Snorkel: Rapid Training Data Creation with Weak Supervision
Labeling training data is increasingly the largest bottleneck in deployi...
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09/10/2017
Robust Sparse Coding via Self-Paced Learning
Sparse coding (SC) is attracting more and more attention due to its comp...
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04/20/2017
SwellShark: A Generative Model for Biomedical Named Entity Recognition without Labeled Data
We present SwellShark, a framework for building biomedical named entity ...
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05/25/2016
Data Programming: Creating Large Training Sets, Quickly
Large labeled training sets are the critical building blocks of supervis...
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02/03/2015