{"total":28,"rows":[{"id":"2104.09987","title":"Differentiable Model Compression via Pseudo Quantization Noise","created":"2021-04-20","cited_by_count":45,"area":null},{"id":"2108.12659","title":"DKM: Differentiable K-Means Clustering Layer for Neural Network Compression","created":"2021-08-28","cited_by_count":31,"area":null},{"id":"2102.07981","title":"SiMaN: Sign-to-Magnitude Network Binarization","created":"2021-02-16","cited_by_count":18,"area":null},{"id":"2109.02100","title":"Cluster-Promoting Quantization with Bit-Drop for Minimizing Network Quantization Loss","created":"2021-09-05","cited_by_count":12,"area":null},{"id":"2205.14283","title":"Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling","created":"2022-05-28","cited_by_count":12,"area":null},{"id":"2110.13220","title":"Demystifying and Generalizing BinaryConnect","created":"2021-10-25","cited_by_count":11,"area":null},{"id":"2112.15139","title":"Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks","created":"2021-12-30","cited_by_count":9,"area":null},{"id":"2107.03453","title":"$S^3$: Sign-Sparse-Shift Reparametrization for Effective Training of Low-bit Shift Networks","created":"2021-07-07","cited_by_count":7,"area":null},{"id":"2201.13361","title":"Signing the Supermask: Keep, Hide, Invert","created":"2022-01-31","cited_by_count":7,"area":null},{"id":"2208.06064","title":"Mixed-Precision Neural Networks: A Survey","created":"2022-08-11","cited_by_count":7,"area":null},{"id":"2110.00276","title":"TyXe: Pyro-based Bayesian neural nets for Pytorch","created":"2021-10-01","cited_by_count":6,"area":null},{"id":"2110.02998","title":"Federated Learning via Plurality Vote","created":"2021-10-06","cited_by_count":6,"area":null},{"id":"2201.10360","title":"Resource-efficient Deep Neural Networks for Automotive Radar Interference Mitigation","created":"2022-01-25","cited_by_count":6,"area":null},{"id":"2105.12344","title":"Probabilistic Selective Encryption of Convolutional Neural Networks for Hierarchical Services","created":"2021-05-26","cited_by_count":5,"area":null},{"id":"2208.09708","title":"DenseShift: Towards Accurate and Efficient Low-Bit Power-of-Two Quantization","created":"2022-08-20","cited_by_count":5,"area":null},{"id":"2107.05298","title":"HEMP: High-order Entropy Minimization for neural network comPression","created":"2021-07-12","cited_by_count":4,"area":null},{"id":"2110.03549","title":"Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators","created":"2021-10-07","cited_by_count":4,"area":null},{"id":"2212.12653","title":"Hyperspherical Quantization: Toward Smaller and More Accurate Models","created":"2022-12-24","cited_by_count":4,"area":null},{"id":"2302.07612","title":"Towards Optimal Compression: Joint Pruning and Quantization","created":"2023-02-15","cited_by_count":4,"area":null},{"id":"2303.01505","title":"Ternary Quantization: A Survey","created":"2023-03-02","cited_by_count":2,"area":null},{"id":"2307.14193","title":"Efficient Learning of Discrete-Continuous Computation Graphs","created":"2023-07-26","cited_by_count":2,"area":null},{"id":"2401.16760","title":"One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training","created":"2024-01-30","cited_by_count":2,"area":null},{"id":"2307.14151","title":"Learning Disentangled Discrete Representations","created":"2023-07-26","cited_by_count":1,"area":null},{"id":"2107.10998","title":"Pruning Ternary Quantization","created":"2021-07-23","cited_by_count":0,"area":null},{"id":"2204.01935","title":"Nonlocal optimization of binary neural networks","created":"2022-04-05","cited_by_count":0,"area":null},{"id":"2307.01683","title":"Learning Discrete Weights and Activations Using the Local Reparameterization Trick","created":"2023-07-04","cited_by_count":0,"area":null},{"id":"2411.00273","title":"Efficient Model Compression for Bayesian Neural Networks","created":"2024-11-01","cited_by_count":0,"area":null},{"id":"2510.08999","title":"SQS: Bayesian DNN Compression through Sparse Quantized Sub-distributions","created":"2025-10-10","cited_by_count":0,"area":null}],"next_cursor":null}