154 citations · 717 across the 63 of their papers we have counts for
13 papers · 1 filter
Bayesian interpretation of SGD as Ito process
Soma Yokoi, Issei Sato
The current interpretation of stochastic gradient descent (SGD) as a stochastic process lacks generality in that its numerical scheme restricts continuous-time dynamics as well as…
Classification from Triplet Comparison Data
Zhenghang Cui, Nontawat Charoenphakdee, Issei Sato +1
Learning from triplet comparison data has been extensively studied in the context of metric learning, where we want to learn a distance metric between two instances, and ordinal em…
Interactive Optimization of Generative Image Modeling using Sequential Subspace Search and Content-based Guidance
Toby Chong Long Hin, I-Chao Shen, Issei Sato +1
Generative image modeling techniques such as GAN demonstrate highly convincing image generation result. However, user interaction is often necessary to obtain the desired results.…
Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping
Xi Yang, Bojian Wu, Issei Sato +1
Deep neural networks (DNNs) have a high accuracy on image classification tasks. However, DNNs trained by such dataset with co-occurrence bias may rely on wrong features while makin…
Solving NP-Hard Problems on Graphs with Extended AlphaGo Zero
Kenshin Abe, Zijian Xu, Issei Sato +1
There have been increasing challenges to solve combinatorial optimization problems by machine learning. Khalil et al. proposed an end-to-end reinforcement learning framework, S2V-D…
Classification from Pairwise Similarities/Dissimilarities and Unlabeled Data via Empirical Risk Minimization
Takuya Shimada, Han Bao, Issei Sato +1
Pairwise similarities and dissimilarities between data points might be easier to obtain than fully labeled data in real-world classification problems, e.g., in privacy-aware situat…