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08/24/2023
Disentanglement Learning via Topology
We propose TopDis (Topological Disentanglement), a method for learning d...
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01/31/2023
Learning Topology-Preserving Data Representations
We propose a method for learning topology-preserving data representation...
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10/17/2022
Data-Driven Short-Term Daily Operational Sea Ice Regional Forecasting
Global warming made the Arctic available for marine operations and creat...
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08/31/2022
QuantNAS for super resolution: searching for efficient quantization-friendly architectures against quantization noise
There is a constant need for high-performing and computationally efficie...
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12/31/2021
Representation Topology Divergence: A Method for Comparing Neural Network Representations
Comparison of data representations is a complex multi-aspect problem tha...
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06/08/2021
Manifold Topology Divergence: a Framework for Comparing Data Manifolds
We develop a framework for comparing data manifolds, aimed, in particula...
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12/31/2020
Topological obstructions in neural networks learning
We apply methods of topological data analysis to loss functions to gain ...
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06/15/2020
Multi-fidelity Neural Architecture Search with Knowledge Distillation
Neural architecture search (NAS) targets at finding the optimal architec...
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06/12/2020
NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing
Neural Architecture Search (NAS) is a promising and rapidly evolving res...
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09/25/2018
Inferring Complementary Products from Baskets and Browsing Sessions
Complementary products recommendation is an important problem in e-comme...
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11/07/2016
Distributed Coordinate Descent for Generalized Linear Models with Regularization
Generalized linear model with L_1 and L_2 regularization is a widely use...
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12/20/2014
Using Neural Networks for Click Prediction of Sponsored Search
Sponsored search is a multi-billion dollar industry and makes up a major...
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11/24/2014