Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities
We apply the derived computational error bounds to study the generalization performance ofmulti-pass stochastic gradient descent (SGD) ina non-parametric setting.
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- Asia > China > Guangdong Province > Shenzhen (0.04)
Counterfactual Fairness by Combining Factual and Counterfactual Predictions
Counterfactual Fairness (CF), which posits that an ML model's outcome on any individual should remain unchanged if they had belonged to a different demographic
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A Neural Compositional Paradigm for Image Captioning
Bo Dai, Sanja Fidler, Dahua Lin
Neural Information Processing Systems http://nips.cc/
- Information Technology > Artificial Intelligence > Vision (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
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- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.52)
Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy Functions
Chris Russell, Matteo Toso, Neill Campbell
Neural Information Processing Systems http://nips.cc/
From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces Peter Shaw
Much of the previous work towards digital agents for graphical user interfaces (GUIs) has relied on text-based representations (derived from HTML or other structured data sources), which are not always readily available.
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Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test
Lizhong Ding, Mengyang Yu, Li Liu, Fan Zhu, Yong Liu, Yu Li, Ling Shao
Learning the probability distribution of high-dimensional data is a challenging problem.
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Multi-armed Bandits with Compensation
Neural Information Processing Systems http://nips.cc/
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- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Information Technology > Artificial Intelligence > Machine Learning (1.00)
- Information Technology > Data Science > Data Mining > Big Data (0.84)
- North America > United States > Virginia (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Asia > China > Hong Kong (0.04)
- Asia > China > Guangdong Province (0.04)
Estimating Learnability in the Sublinear Data Regime
Neural Information Processing Systems http://nips.cc/
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A Fourier Perspective on Model Robustness in Computer Vision
Dong Yin, Raphael Gontijo Lopes, Jon Shlens, Ekin Dogus Cubuk, Justin Gilmer
Achieving robustness to distributional shift is a longstanding and challenging goal of computer vision.
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