Results 61 to 70 of about 31,077 (302)

Vertical Differentiation and Collusion: Pruning or Proliferation? [PDF]

, 2016
n this paper, we tackle the dilemma of pruning versus proliferation in a vertically differentiated oligopoly under the assumption that some firms collude and control both the range of variants for sale and their corresponding prices, likewise a ...
Jaskold Gabszewicz, Jean, Marini, Marco A., Jean Gabszewicz, Jean, TAROLA, Ornella, Gabszewicz, Jean J., MARINI, MARCO   +5 more
core   +1 more source

Kinsenoside Targets IDH1 to Restore Microglial Immune‐Metabolic Homeostasis for Alzheimer's Disease Therapy

Advanced Science, EarlyView.
Dysregulated TCA cycle contributes to Alzheimer's disease (AD) pathogenesis. Here, we show that microglial isocitrate dehydrogenase 1 (IDH1) is a critical driver. Elevated IDH1 disrupts citrate metabolism and mitochondrial function, exacerbating AD pathology.
Qianqian Li, Yajin Liao, Yan‐bo Zhao, Hongxing Wu, Tong Jin, Shuoshuo Li, Yuhan Liu, Peng Li, Songying Ouyang, Zekai Li, YuTing Xia, Qian Hua, Rui‐Yuan Pan, Zengqiang Yuan   +13 more
wiley   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

Advanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu, Rui Qiao, Ying Li, Junhong Li, Nuoya Yue, Jing Ge, Jiao Wang, Luonan Chen, Peiluan Li   +8 more
wiley   +1 more source

A flexible pruning on deep convolutional neural networks

Dianxin kexue, 2022
Despite the successful application of deep convolutional neural networks, due to the redundancy of its structure, the large memory requirements and the high computing cost lead it hard to be well deployed to the edge devices with limited resources ...
Liang CHEN, Yaguan QIAN, Zhiqiang HE, Xiaohui GUAN, Bin WANG, Xing WANG   +5 more
doaj   +2 more sources

Visual SLAM Based on Improved Line Filtering Decision and Weight Optimization

IEEE Access
In recent years, visual SLAM (Simultaneous Localization and Mapping) based on line feature tracking has garnered widespread attention due to its provision of additional constraints for structured scenes. However, the current mainstream framework, PL-VINS,
Yibo Cao, Zehao Luo, Zhenyu Deng
doaj   +1 more source

PhosSight: A Unified Deep Learning Framework Boosting and Accelerating Phosphoproteome Identification to Enable Biological Discoveries

Advanced Science, EarlyView.
PhosSight is a unified deep‐learning framework for phosphoproteome identification, featured by a phosphorylation‐aware detectability predictor. It improves identification sensitivity in DDA through deep re‐localization and rescoring, accelerates DIA searches by detectability‐guided spectral library pruning, and expands phosphoproteome coverage to ...
Ben Wang, Zhiyuan Cheng, Chengying She, Hongwei Zhao, Jiahui Zhang, Lin Lv, Zhihao Yan, Hongwen Zhu, Lizhuang Liu, Yan Fu, Xinpei Yi   +10 more
wiley   +1 more source

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification

Since high resolution remote sensing image classifi-cation often requires a relatively high computation complexity, lightweight models tend to be practical and efficient. Model pruning is an effective method for model compression.
Zou, G, Zhang, C, Liu, F, Chen, N, Yao, L, Li, X, Zhou, J, Xu, S   +7 more
core   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

Efficient Data Pruning via Early-Stage Prediction Stability and Balanced Sampling

IEEE Access
Recently, deep learning has achieved remarkable performance gains across a wide range of vision tasks, largely driven by increasingly large-scale training datasets.
Chih-Yao Hu, Po-Yung Chou, Cheng-Hung Lin   +2 more
doaj   +1 more source

Structure Pruning Strategies for Min-Max Modular Network [PDF]

, 2005
The min-max modular network has been shown to be an efficient classifier, especially in solving large-scale and complex pattern classification problems. Despite its high modularity and parallelism, it suffers from quadratic complexity in space when a multiple-class problem is decomposed into a number of linearly separable problems.
Yang Yang 0030, Bao-Liang Lu
openaire   +1 more source