{"total":22,"rows":[{"id":"2211.14627","title":"Where to Pay Attention in Sparse Training for Feature Selection?","created":"2022-11-26","cited_by_count":15,"area":null},{"id":"2102.09050","title":"End-to-end learnable EEG channel selection for deep neural networks with Gumbel-softmax","created":"2021-02-11","cited_by_count":12,"area":null},{"id":"2303.07200","title":"Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks","created":"2023-03-10","cited_by_count":7,"area":null},{"id":"2204.01682","title":"Deep Feature Screening: Feature Selection for Ultra High-Dimensional Data via Deep Neural Networks","created":"2022-04-04","cited_by_count":6,"area":null},{"id":"2211.06302","title":"GCondNet: A Novel Method for Improving Neural Networks on Small High-Dimensional Tabular Data","created":"2022-11-11","cited_by_count":6,"area":null},{"id":"2211.15616","title":"Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data","created":"2022-11-28","cited_by_count":6,"area":null},{"id":"2405.19221","title":"Domain adaptation in small-scale and heterogeneous biological datasets","created":"2024-05-29","cited_by_count":5,"area":null},{"id":"2408.04583","title":"Unveiling the Power of Sparse Neural Networks for Feature Selection","created":"2024-08-08","cited_by_count":3,"area":null},{"id":"2304.02383","title":"How good Neural Networks interpretation methods really are? A quantitative benchmark","created":"2023-04-05","cited_by_count":2,"area":null},{"id":"2304.03202","title":"SLM: End-to-end Feature Selection via Sparse Learnable Masks","created":"2023-04-06","cited_by_count":1,"area":null},{"id":"2306.15661","title":"Enhancing Representation Learning on High-Dimensional, Small-Size Tabular Data: A Divide and Conquer Method with Ensembled VAEs","created":"2023-06-27","cited_by_count":1,"area":null},{"id":"2402.10641","title":"A Predictive Surrogate Model for Heat Transfer of an Impinging Jet on a Concave Surface","created":"2024-02-16","cited_by_count":1,"area":null},{"id":"2406.01162","title":"Conditional Gumbel-Softmax for constrained feature selection with application to node selection in wireless sensor networks","created":"2024-06-03","cited_by_count":1,"area":null},{"id":"2106.02197","title":"Top-$k$ Regularization for Supervised Feature Selection","created":"2021-06-04","cited_by_count":0,"area":null},{"id":"2107.00816","title":"Few-shot Learning for Unsupervised Feature Selection","created":"2021-07-02","cited_by_count":0,"area":null},{"id":"2201.12910","title":"Sparse Centroid-Encoder: A Nonlinear Model for Feature Selection","created":"2022-01-30","cited_by_count":0,"area":null},{"id":"2206.13968","title":"Information Entropy Initialized Concrete Autoencoder for Optimal Sensor Placement and Reconstruction of Geophysical Fields","created":"2022-06-28","cited_by_count":0,"area":null},{"id":"2306.04795","title":"Feature Selection using Sparse Adaptive Bottleneck Centroid-Encoder","created":"2023-06-07","cited_by_count":0,"area":null},{"id":"2306.04824","title":"Sparse Linear Centroid-Encoder: A Convex Method for Feature Selection","created":"2023-06-07","cited_by_count":0,"area":null},{"id":"2312.15055","title":"Deep Learning for Efficient GWAS Feature Selection","created":"2023-12-22","cited_by_count":0,"area":null},{"id":"2403.14139","title":"Genetic Programming for Explainable Manifold Learning","created":"2024-03-21","cited_by_count":0,"area":null},{"id":"2405.02534","title":"A Multi-Domain Multi-Task Approach for Feature Selection from Bulk RNA Datasets","created":"2024-05-04","cited_by_count":0,"area":null}],"next_cursor":null}