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Secure Data Sharing With Flow Model
In the classical multi-party computation setting, multiple parties joint...
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Inject Machine Learning into Significance Test for Misspecified Linear Models
Due to its strong interpretability, linear regression is widely used in ...
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Adversarial Data Encryption
In the big data era, many organizations face the dilemma of data sharing...
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Learning-Based Low-Rank Approximations
We introduce a "learning-based" algorithm for the low-rank decomposition...
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System-Level Development of a User-Integrated Semi-Autonomous Lawn Mowing System: Problem Overview, Basic Requirements, and Proposed Architecture
This concept paper outlines some recent efforts toward the design and de...
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A Stratified Approach to Robustness for Randomly Smoothed Classifiers
Strong theoretical guarantees of robustness can be given for ensembles o...
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Asymmetric Valleys: Beyond Sharp and Flat Local Minima
Despite the non-convex nature of their loss functions, deep neural netwo...
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An empirical study on evaluation metrics of generative adversarial networks
Evaluating generative adversarial networks (GANs) is inherently challeng...
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An Alternative View: When Does SGD Escape Local Minima?
Stochastic gradient descent (SGD) is widely used in machine learning. Al...
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Hyperparameter Optimization: A Spectral Approach
We give a simple, fast algorithm for hyperparameter optimization inspire...
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Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters
The amount of data available in the world is growing faster than our abi...
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Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling
Accelerated coordinate descent is widely used in optimization due to its...
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Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives
Many classical algorithms are found until several years later to outlive...
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Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition
We analyze stochastic gradient descent for optimizing non-convex functio...
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