185 citations · 945 across the 83 of their papers we have counts for
8 papers · 1 filter
Adam Induces Implicit Weight Sparsity in Rectifier Neural Networks
Atsushi Yaguchi, Taiji Suzuki, Wataru Asano +3
In recent years, deep neural networks (DNNs) have been applied to various machine leaning tasks, including image recognition, speech recognition, and machine translation. However,…
Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality
Taiji Suzuki
Deep learning has shown high performances in various types of tasks from visual recognition to natural language processing, which indicates superior flexibility and adaptivity of d…
Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation
Tomoya Murata, Taiji Suzuki
We develop new stochastic gradient methods for efficiently solving sparse linear regression in a partial attribute observation setting, where learners are only allowed to observe a…
Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error
Taiji Suzuki, Hiroshi Abe, Tomoya Murata +6
Compression techniques for deep neural network models are becoming very important for the efficient execution of high-performance deep learning systems on edge-computing devices. T…
Stochastic Gradient Descent with Exponential Convergence Rates of Expected Classification Errors
Atsushi Nitanda, Taiji Suzuki
We consider stochastic gradient descent and its averaging variant for binary classification problems in a reproducing kernel Hilbert space. In the traditional analysis using a cons…
Cross-domain Recommendation via Deep Domain Adaptation
Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu +2
The behavior of users in certain services could be a clue that can be used to infer their preferences and may be used to make recommendations for other services they have never use…