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TRANSFERRING LEARNING TRAJECTORIES OF NEURAL NETWORKS 12

TRANSFERRING LEARNING TRAJECTORIES OF NEURAL NETWORKS

引用

12th International Conference on Learning Representations, ICLR 2024

作者： Chijiwa, Daiki NTT Computer and Data Science Laboratories NTT Corporation Japan

Training deep neural networks (DNNs) is computationally expensive, which is problematic especially when performing duplicated or similar training runs in model ensemble or fine-tuning pre-trained models, for example. Once we have trained one DNN on some dataset, we have its learning trajectory (i.e., a sequence of intermediate parameters during training) which may potentially contain useful information for learning the dataset. However, there has been no attempt to utilize such information of a given learning trajectory for another training. In this paper, we formulate the problem of "transferring" a given learning trajectory from one initial parameter to another one (named learning transfer problem) and derive the first algorithm to approximately solve it by matching gradients successively along the trajectory via permutation symmetry. We empirically show that the transferred parameters achieve non-trivial accuracy before any direct training, and can be trained significantly faster than training from scratch. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Deep neural networks

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Toward data Efficient Model Merging between Different datasets without Performance Degradation 16

Toward Data Efficient Model Merging between Different Datase...

引用

16th Asian Conference on Machine Learning, ACML 2024

作者： Yamada, Masanori Yamashita, Tomoya Yamaguchi, Shin’ya Chijiwa, Daiki NTT Social Informatics Laboratories Japan NTT Computer and Data Science Laboratories Japan

Model merging is attracting attention as a novel method for creating a new model by combining the weights of different trained models. While previous studies reported that model merging works well for models trained on a single dataset with different random seeds, model merging between different datasets remains unsolved. In this paper, we attempt to reveal the difficulty in merging such models trained on different datasets and alleviate it. Our empirical analyses show that, in contrast to the single-dataset scenarios, dataset information needs to be accessed to achieve high accuracy when merging models trained on different datasets. However, the requirement to use full datasets not only incurs significant computational costs but also becomes a major limitation when integrating models developed and shared by others. To address this, we demonstrate that dataset reduction techniques, such as coreset selection and dataset condensation, effectively reduce the data requirement for model merging. In our experiments with SPLIT-CIFAR10 model merging, the accuracy is significantly improved by 31% when using the full dataset and 24% when using the sampled subset compared with not using the dataset. Our code is available at this URL. © 2024 M. Yamada, T. Yamashita, S. Yamaguchi & D. Chijiwa.

关键词： data accuracy

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Towards N-version Quantum Software Systems for Reliable Classical-Quantum Computing 35

Towards N-version Quantum Software Systems for Reliable Clas...

引用

35th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2024

作者： Saito, Shinobu Endo, Suguru Suzuki, Yasunari Ntt Computer and Data Science Laboratories Tokyo Japan

ISBN: (纸本)9798350367041

While quantum computers have attracted much attention, dealing with computational errors due to noise effects caused by the interaction between quantum hardware and the external environment is a significant challenge. In this paper, we propose an approach to apply N-version programming (NVP) to quantum software to improve the reliability of the entire quantum software system. First, we define architecture patterns for N-version quantum software systems (NVQS) based on a combination of quantum libraries and devices. Next, given that the output of the quantum software system is a probability distribution, we came up with an evaluation strategy inspired by the concept of NVP for clustering and selecting multiple probability distributions output from NVQS. Finally, we outline our future experimental plan. © 2024 IEEE.

关键词： Quantum computers

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Learning Robust Convolutional Neural Networks with Relevant Feature Focusing Via Explanations

Learning Robust Convolutional Neural Networks with Relevant ...

引用

2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Adachi, Kazuki Yamaguchi, Shin'ya Ntt Corporation Computer and Data Science Laboratories Japan

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Existing image recognition techniques based on convolutional neural networks (CNNs) basically assume that the training and test datasets are sampled from i.i.d distributions. However, this assumption is easily broken in the real world because of the distribution shift that occurs when the co-occurrence relations between objects and backgrounds in input images change. Under this type of distribution shift, CNNs learn to focus on features that are not task-relevant, such as backgrounds from the training data, and degrade their accuracy on the test data. To tackle this problem, we propose relevant feature focusing (ReFF). ReFF detects task-relevant features and regularizes CNNs via explanation outputs (e.g., Grad-CAM). Since ReFF is composed of post-hoc explanation modules, it can be easily applied to off-the-shelf CNNs. Furthermore, ReFF requires no additional inference cost at test time because it is only used for regularization while training. We demonstrate that CNNs trained with ReFF focus on features relevant to the target task and that ReFF improves the test-time accuracy. © 2022 IEEE.

关键词： Convolutional neural networks

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Deep Quantigraphic Image Enhancement via Comparametric Equations 48

Deep Quantigraphic Image Enhancement via Comparametric Equat...

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Wu, Xiaomeng Sun, Yongqing Kimura, Akisato Ntt Corporation Communication Science Laboratories Japan Ntt Corporation Computer and Data Science Laboratories Japan

ISBN: (纸本)9781728163277

Most recent methods of deep image enhancement can be generally classified into two types: decompose-and-enhance and illumination estimation-centric. The former is usually less efficient, and the latter is constrained by a strong assumption regarding image reflectance as the desired enhancement result. To alleviate this constraint while retaining high efficiency, we propose a novel trainable module that diversifies the conversion from the low-light image and illumination map to the enhanced image. It formulates image enhancement as a comparametric equation parameterized by a camera response function and an exposure compensation ratio. By incorporating this module in an illumination estimation-centric DNN, our method improves the flexibility of deep image enhancement, limits the computational burden to illumination estimation, and allows for fully unsupervised learning adaptable to the diverse demands of different tasks. © 2023 IEEE.

关键词： Image enhancement

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Efficient Network Representation Learning via Cluster Similarity 28th

Efficient Network Representation Learning via Cluster Simil...

引用

28th International Conference on database Systems for Advanced Applications, DASFAA 2023

作者： Fujiwara, Yasuhiro Ida, Yasutoshi Kumagai, Atsutoshi Nakano, Masahiro Kimura, Akisato Ueda, Naonori NTT Communication Science Laboratories Kanagawa Atsugi Japan NTT Computer and Data Science Laboratories Tokyo Musashino Japan

ISBN: (纸本)9783031306747

Network representation learning is a de-facto tool for graph analytics. The mainstream of the previous approaches is to factorize the proximity matrix between nodes. However, if n is the number of nodes, since the size of the proximity matrix is n× n, it needs O(n3) time and O(n2) space to perform network representation learning. The proposed approach computes the representations of the clusters from similarities between clusters and computes the representations of nodes by referring to them. If l is the number of clusters, since l n, we can efficiently obtain the representations of clusters from a small l× l similarity matrix. Experiments show that our approach can perform network representation learning more efficiently and effectively than existing approaches. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Algorithm Efficient Network representation learning

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Moiré Reduction Method for Visually Equivalent Light Field Display Using Special Barrier Aperture Structure 29

Moiré Reduction Method for Visually Equivalent Light Field ...

引用

29th International Display Workshops, IDW 2022

作者： Date, Munekazu Mitasaki, Tokinobu Matsumoto, Ayumi Kitahara, Masaki NTT Computer and Data Science Laboratories Nippon Telegraph and Telephone Corporation Japan

A visually equivalent light field 3D (VELF3D) display is a parallax-barrier-type autostereoscopic 3D display. Since stripes of the barrier and pixels are in parallel, moiré occurred, when the barrier is placed on the screen. In this paper, we suppressed moiré by only providing unevenness in the aperture shape of the barrier. © 2022 ITE and SID.

关键词： Three dimensional displays

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Improving Raft Performance with Bulk Transfers 11

Improving Raft Performance with Bulk Transfers

引用

11th International Symposium on Computing and Networking Workshops, CANDARW 2023

作者： Yamashita, Aoi Tanaka, Masahiro Bessho, Yutaro Fujiwara, Yasuhiro Kawashima, Hideyuki Graduate School of Keio University Japan Ntt Computer and Data Science Laboratories Japan Ntt Communication Science Laboratories Japan Keio University Japan

ISBN: (纸本)9798350306941

Raft is known as a replicating state machine that tolerates crash faults, and its use enables various distributed systems, including distributed transaction processing systems. The original Raft protocol creates an intra-cluster consensus by having the leader generate a log of each incoming client request and replicate it to its followers. When requests arrive frequently, the number of replications increases, increasing the number of communications and possibly leading to performance degradation. To solve this problem, we propose a bulk-transfer protocol that replicates multiple requests at once. We implemented the Raft system to verify the effect of the proposed method. We measured the performance of the implemented system when multiple requests were transferred in bulk and observed an increase in throughput with an increase in the amount of data replicated at a time. The highest throughput of 214 MB/sec was achieved when replicating 12.5 MB at a time. This is 12,066 times higher than the performance when replicating one request (18 B) at a time. Besides, the size of the log is reduced to 5/9 of the conventional method. © 2023 IEEE.

关键词： Distributed computer systems

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Visually Equivalent Light Field 3-D for Portable Displays

Visually Equivalent Light Field 3-D for Portable Displays

引用

作者： Date, Munekazu Shimizu, Shinya Yamamoto, Susumu Nippon Telegraph and Telephone Corporation Ntt Computer and Data Science Laboratories Yokosuka239-0847 Japan Ntt Computer and Data Science Laboratories Yokosuka239-0847 Japan Nippon Telegraph and Telephone Corporation Ntt Human Informatics Laboratories Tokyo108-0023 Japan

Highly realistic 3-D displays that can reproduce object images to look like physical objects are utilized for natural and correct remote operation in industrial scenes. Therefore, we developed a visually equivalent light field 3-D (VELF3D) display that can produce highly realistic, accurate images with a high resolution and a smooth, accurate motion parallax. However, the observation distance is slightly long, and users cannot reach the displayed images. Therefore, we aim to develop a tablet-computer-type VELF3D display that enables users to touch the displayed objects. The display viewpoint density has been increased to achieve a shorter observation distance, while maintaining the display depth range. Because higher resolutions are required for a close observation distance and increased display viewpoints, we aimed to improve the effective resolution using almost the same pixel pitch display panel. Therefore, we built a prototype that combines a vertical red, green, blue stripe display panel and a parallax barrier with subpixel width slits. We confirmed effective resolution improvement by tiny subjective tests. This method also helps increase the depth range of the display when it is observed from a normal distance. © 1972-2012 IEEE.

关键词： Three dimensional displays

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A Seat Headrest Loudspeaker System with Personalized Sound Zone Capabilities

A Seat Headrest Loudspeaker System with Personalized Sound Z...

引用

2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Fukui, Masahiro Kobayashi, Kazunori Kamado, Noriyoshi Computer and Data Science Laboratories NTT Corporation Tokyo Japan NTT Sonority Inc Product Department Tokyo Japan

ISBN: (纸本)9798350324136

This paper proposes a novel local reproduction method called 'personalized sound zone,' which can confine a sound field by using a combination of software processing and hardware innovations that remove loudspeaker enclosures from an array, and discusses the development of a headrest loudspeaker prototype unit not to leak sound into adjacent seats for airline seating. The proposed method is based on a two-channel fixed beamforming algorithm that does not require extensive equipment, and its prototype is compact enough to fit in a seat headrest. The personalized sound zone software algorithm is implemented on a DSP circuit board and processed in real time. © 2024 IEEE.

关键词： enclosureless loudspeaker fixed beamforming array local sound field reproduction seat headrest

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