AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment

Neural architecture search (NAS) is an approach for automatically designing a neural network architecture without human effort or expert knowledge. However, the high computational cost of NAS limits its use in commercial applications. Two recent NAS paradigms, namely one-shot and sparse propagation, which reduce the time and space complexities, respectively, provide clues for solving this problem. In this paper, we propose a novel search strategy for one-shot and sparse propagation NAS, namely AdvantageNAS, which further reduces the time complexity of NAS by reducing the number of search iterations. AdvantageNAS is a gradient-based approach that improves the search efficiency by introducing credit assignment in gradient estimation for architecture updates. Experiments on the NAS-Bench-201 and PTB dataset show that AdvantageNAS discovers an architecture with higher performance under a limited time budget compared to existing sparse propagation NAS. To further reveal the reliabilities of AdvantageNAS, we investigate it theoretically and find that it monotonically improves the expected loss and thus converges.Comment: preprint to be published in AAAI-2

Removal of defects in a colloidal crystal grown in an inverted pyramidal container by changing the external force

Keeping the formation of colloidal crystals by sedimentation in mind, we carry out Brownian dynamics simulations and study the crystallization of colloidal particles in an inverted pyramidal container. When an external force is added, the sedimentation of particles occurs and the particle density increases in the low region of the inverted pyramidal container. The crystallization of particles occurs and the face-centered cubic structure is formed in the container. When the force is large, the particles with the hexagonal close-packed structure are formed. Disordered particles are also formed and act as defects in bulk. After the sedimentation finishes, we decrease the force transiently. The defects in bulk are removed from the bulk. © 2015 The Japan Society of Applied Physics.Embargo Period 12 month

Crystallization of Brownian particles in a pyramidal pit by a uniform external force

We carry out Brownian dynamics simulations and study the crystallization of particles in an inverse pyramidal-shaped container induced by an external force. Owing to the side walls of the container, the face-centered cubic (fcc) structure is mainly formed. In the bulk, both disordered solidlike particles and hexagonal close-packed (hcp) structured particles are hardly formed. These two types of particle appear near the central axis of the container. Their numbers increase with increasing strength of the external force. ©2015 The Physical Society of Japan

Dependence of the apex angle of an inverted pyramidal-shaped container on crystallization of Brownian particles

Large grains of a close-packed colloidal crystal have been experimentally shown to form in an inverted pyramidal pit by sedimentation [S. Matsuo et al., Appl. Phys. Lett. 82, 4285 (2003)]. Keeping this experiment in mind, we study the crystallization of Brownian particles. We carry out Brownian dynamics simulations in an inverted pyramidal-shaped container. The Brownian particles settle out toward the apex of the container by a uniform external force. If the apex angle is suitable, large grains with the face-centered cubic (fcc) structure are formed [Y. Kanatsu and M. Sato, J. Phys. Soc. Jpn. 84, 044601 (2015)]. When the apex angle deviates from a suitable value, the number of hexagonal closepacked (hcp) structured particles, Nhcp, increases with increasing angle deviation. The formation of the hcp structure is induced by disordered particles remaining in the center region of the container. Copyright © 2015 The Physical Society of Japan.Embargo Period 12 month

Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification

In the field of reinforcement learning, because of the high cost and risk of policy training in the real world, policies are trained in a simulation environment and transferred to the corresponding real-world environment. However, the simulation environment does not perfectly mimic the real-world environment, lead to model misspecification. Multiple studies report significant deterioration of policy performance in a real-world environment. In this study, we focus on scenarios involving a simulation environment with uncertainty parameters and the set of their possible values, called the uncertainty parameter set. The aim is to optimize the worst-case performance on the uncertainty parameter set to guarantee the performance in the corresponding real-world environment. To obtain a policy for the optimization, we propose an off-policy actor-critic approach called the Max-Min Twin Delayed Deep Deterministic Policy Gradient algorithm (M2TD3), which solves a max-min optimization problem using a simultaneous gradient ascent descent approach. Experiments in multi-joint dynamics with contact (MuJoCo) environments show that the proposed method exhibited a worst-case performance superior to several baseline approaches.Comment: Neural Information Processing Systems 2022 (NeurIPS '22

Development of an Evolutionary Three-Dimensional Scroll Compressor

A novel three-dimensional scroll compressor was developed. The authors have produced 3D scroll compressor since 2004. The 3D scroll is able to compress refrigerant in axial direction as well as in existing radial direction by employing steps at the bottom and the tip of the scroll which change the height of compression chamber on the middle of the compression process. For the purpose of further performance improvement, the authors developed an evolutionary three-dimensional compression mechanism, named e-3D scroll . The e-3D scroll is equipped with a sloped tip and a sloped end plate in each scroll instead of the steps in the conventional 3D scroll. The height of compression chamber decreases continuously with progression of compression by the sloped shape. The e-3D scroll achieved considerable efficiency improvement compared to the conventional 3D scroll since there is no leakage loss in the steps while keeping the advantages of high compression ratio, large capacity and small size by the sloped tip and end plate. In addition, the noise and vibration of the e-3D scroll compressor reduced significantly since the rate of change of cylinder volume throughout the compression process and the torque variation in the rotation became smaller than the conventional 3D scroll. This article describes the compression mechanism and the performance improvement technology in the e-3D scroll

Dependence of crystallization of Brownian particles by sedimentation on the force direction

The formation of a large close-packed colloidal crystal with the fcc structure was observed during the sedimentation of colloidal particles in an inverted pyramidal pit [S. Matsuo et al., Appl. Phys. Lett. 82, 4285 (2003)]. Carrying out Brownian dynamics simulations, we confirmed that large grains with the fcc structure are formed when the apex angle of the inverted pyramidal container is suitable and the force direction is parallel to the the center axis [Y. Kanatsu and M. Sato, J. Phys. Soc. Jpn. 84, 044601 (2015)]. To form a high-quality colloidal crystal without defects, it is important to investigate in detail how the quality of a colloidal crystal is affected by the force direction and container shape. In this paper, we focus on the effect of the force direction on crystal quality and investigate how the ratio of the number of the hcp structured particles, Nhcp, to that of fcc structured particles, Nfcc, is affected by the force direction. In our simulation, the ratio of Nfcc to Nhcp is hardly changed when the force direction deviates from the central axis: Nfcc is much larger than Nhcp irrespective of the force direction. Thus, our results show that the crystal structure is insensitive to the force direction in forming a colloidal crystal by sedimentation in an inverted pyramidal container. © 2015 The Japan Society of Applied Physics.Embargo Period 12 month