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Found 9 papers, 3 papers with code
C3-SL: Circular Convolution-Based Batch-Wise Compression for Communication-Efficient Split Learning
Based on the simulation results on CIFAR-10 and CIFAR-100, our method achieves a 16x compression ratio with negligible accuracy drops compared with the vanilla SL.
Learnable Mixed-precision and Dimension Reduction Co-design for Low-storage Activation
Recently, deep convolutional neural networks (CNNs) have achieved many eye-catching results.
MAUS: A Dataset for Mental Workload Assessmenton N-back Task Using Wearable Sensor
Besides, we also presents a reproducible baseline system as a preliminary benchmark (The code of the baseline system on MAUS dataset is available on Github: https://github. com/rickwu11/MAUS\_dataset\_baseline\_system), which testing accuracy are 71. 6 %, 66. 7 %, and 59. 9 % in ECG, fingertip PPG, wristband PPG, respectively.
High-resolution global irrigation prediction with Sentinel-2 30m data
An accurate and precise understanding of global irrigation usage is crucial for a variety of climate science efforts.
Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method
We address the problem of distinguishing cause from effect in bivariate setting.
AdaBoost-assisted Extreme Learning Machine for Efficient Online Sequential Classification
In this paper, we propose an AdaBoost-assisted extreme learning machine for efficient online sequential classification (AOS-ELM).
Deep Learning for Epidemiological Predictions
Predicting new and urgent trends in epidemiological data is an important problem for public health, and has attracted increasing attention in the data mining and machine learning communities.
Integration of LiDAR and Hyperspectral Data for Land-cover Classification: A Case Study
In this paper, an approach is proposed to fuse LiDAR and hyperspectral data, which considers both spectral and spatial information in a single framework.
TF-Label: a Topological-Folding Labeling Scheme for Reachability Querying in a Large Graph
We propose TF-label, an efficient and scalable labeling scheme for processing reachability queries.
