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06/19/2023
Co-design Hardware and Algorithm for Vector Search
Vector search has emerged as the foundation for large-scale information ...
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06/12/2022
Stochastic Gradient Descent without Full Data Shuffle
Stochastic gradient descent (SGD) is the cornerstone of modern machine l...
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04/04/2022
SHiFT: An Efficient, Flexible Search Engine for Transfer Learning
Transfer learning can be seen as a data- and compute-efficient alternati...
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03/08/2022
DeepSE-WF: Unified Security Estimation for Website Fingerprinting Defenses
Website fingerprinting (WF) attacks, usually conducted with the help of ...
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02/24/2022
Learning to Merge Tokens in Vision Transformers
Transformers are widely applied to solve natural language understanding ...
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12/15/2021
Dynamic Human Evaluation for Relative Model Comparisons
Collecting human judgements is currently the most reliable evaluation me...
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08/30/2021
Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee
The Bayes error rate (BER) is a fundamental concept in machine learning ...
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02/17/2021
Decoding EEG Brain Activity for Multi-Modal Natural Language Processing
Until recently, human behavioral data from reading has mainly been of in...
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02/15/2021
A Data Quality-Driven View of MLOps
Developing machine learning models can be seen as a process similar to t...
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10/16/2020
On Automatic Feasibility Study for Machine Learning Application Development with ease.ml/snoopy
In our experience working with domain experts who are using today's Auto...
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10/15/2020
On Convergence of Nearest Neighbor Classifiers over Feature Transformations
The k-Nearest Neighbors (kNN) classifier is a fundamental non-parametric...
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10/13/2020
Which Model to Transfer? Finding the Needle in the Growing Haystack
Transfer learning has been recently popularized as a data-efficient alte...
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09/28/2020
Scalable Transfer Learning with Expert Models
Transfer of pre-trained representations can improve sample efficiency an...
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10/08/2019
Lossy Image Compression with Recurrent Neural Networks: from Human Perceived Visual Quality to Classification Accuracy
Deep neural networks have recently advanced the state-of-the-art in imag...
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03/01/2019
Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment
Continuous integration is an indispensable step of modern software engin...
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10/17/2018
Distributed Learning over Unreliable Networks
Most of today's distributed machine learning systems assume reliable ne...
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09/27/2018
The Convergence of Sparsified Gradient Methods
Distributed training of massive machine learning models, in particular d...
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02/22/2018
