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Featured Co-authors

Torsten Hoefler
137 publications
Xinyu Zhang
106 publications
Rui Chen
77 publications
Richard E. Turner
75 publications
Yutaka Matsuo
57 publications
Ioannis Mitliagkas
46 publications
Kris M. Kitani
40 publications
Mohammad Emtiyaz Khan
37 publications
Chuan Sheng Foo
36 publications
Hirokatsu Kataoka
30 publications
Satoshi Matsuoka
26 publications

∙ 08/29/2023

Reducing shared memory footprint to leverage high throughput on Tensor Cores and its flexible API extension library

NVIDIA Tensor Core is a mixed-precision matrix-matrix multiplication and...

0 Hiroyuki Ootomo, et al. ∙

∙ 07/27/2023

Pre-training Vision Transformers with Very Limited Synthesized Images

Formula-driven supervised learning (FDSL) is a pre-training method that ...

0 Ryo Nakamura, et al. ∙

∙ 06/21/2023

DGEMM on Integer Matrix Multiplication Unit

Deep learning hardware achieves high throughput and low power consumptio...

0 Hiroyuki Ootomo, et al. ∙

∙ 05/08/2023

ASDL: A Unified Interface for Gradient Preconditioning in PyTorch

Gradient preconditioning is a key technique to integrate the second-orde...

0 Kazuki Osawa, et al. ∙

∙ 04/10/2023

Mixed-Precision Random Projection for RandNLA on Tensor Cores

Random projection can reduce the dimension of data while capturing its s...

0 Hiroyuki Ootomo, et al. ∙

∙ 03/15/2023

Quantum Circuit Simulation by SGEMM Emulation on Tensor Cores and Automatic Precision Selection

Quantum circuit simulation provides the foundation for the development o...

0 Hiryuki Ootomo, et al. ∙

∙ 03/02/2023

Visual Atoms: Pre-training Vision Transformers with Sinusoidal Waves

Formula-driven supervised learning (FDSL) has been shown to be an effect...

0 Sora Takashima, et al. ∙

∙ 11/18/2022

Informative Sample-Aware Proxy for Deep Metric Learning

Among various supervised deep metric learning methods proxy-based approa...

0 Aoyu Li, et al. ∙

∙ 11/15/2022

Empirical Study on Optimizer Selection for Out-of-Distribution Generalization

Modern deep learning systems are fragile and do not generalize well unde...

0 Hiroki Naganuma, et al. ∙

∙ 08/23/2022

Scalable Linear Time Dense Direct Solver for 3-D Problems Without Trailing Sub-Matrix Dependencies

Factorization of large dense matrices are ubiquitous in engineering and ...

0 Qianxiang Ma, et al. ∙

∙ 08/12/2022

Parallel QR Factorization of Block Low-Rank Matrices

We present two new algorithms for Householder QR factorization of Block ...

0 M. Ridwan Apriansyah, et al. ∙

∙ 06/18/2022

Replacing Labeled Real-image Datasets with Auto-generated Contours

In the present work, we show that the performance of formula-driven supe...

11 Hirokatsu Kataoka, et al. ∙

∙ 03/07/2022

Recovering single precision accuracy from Tensor Cores while surpassing the FP32 theoretical peak performance

Tensor Core is a mixed-precision matrix-matrix multiplication unit on NV...

0 Hiroyuki Ootomo, et al. ∙

∙ 09/09/2021

OPIRL: Sample Efficient Off-Policy Inverse Reinforcement Learning via Distribution Matching

Inverse Reinforcement Learning (IRL) is attractive in scenarios where re...

29 Hana Hoshino, et al. ∙

∙ 04/01/2021

RePOSE: Real-Time Iterative Rendering and Refinement for 6D Object Pose Estimation

The use of iterative pose refinement is a critical processing step for 6...

3 Shun Iwase, et al. ∙

∙ 07/30/2020

Epipolar-Guided Deep Object Matching for Scene Change Detection

This paper describes a viewpoint-robust object-based change detection ne...

1 Kento Doi, et al. ∙

∙ 02/13/2020

Scalable and Practical Natural Gradient for Large-Scale Deep Learning

Large-scale distributed training of deep neural networks results in mode...

0 Kazuki Osawa, et al. ∙

∙ 10/30/2019

Effect of Mixed Precision Computing on H-Matrix Vector Multiplication in BEM Analysis

Hierarchical Matrix (H-matrix) is an approximation technique which split...

0 Rise Ooi, et al. ∙

∙ 06/06/2019

Practical Deep Learning with Bayesian Principles

Bayesian methods promise to fix many shortcomings of deep learning, but ...

23 Kazuki Osawa, et al. ∙

∙ 11/29/2018

Second-order Optimization Method for Large Mini-batch: Training ResNet-50 on ImageNet in 35 Epochs

Large-scale distributed training of deep neural networks suffer from the...

0 Kazuki Osawa, et al. ∙

∙ 03/27/2018

Extreme Scale FMM-Accelerated Boundary Integral Equation Solver for Wave Scattering

Algorithmic and architecture-oriented optimizations are essential for ac...

0 Mustafa AbdulJabbar, et al. ∙

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