Description
Book SynopsisFreeFlow: A Unified Viewpoint on Diffusion Probabilistic Models via Optimal Transport and Fluid Mechanics.- Optimizing CNNs with Gram Schmidt Non-Iterative Learning for Image Recognition.- Improving Multilingual Speech Recognition with Tucker-compressed Mixture of LoRAs.- MetaFix: Semi-Supervised Model Agnostic Meta-Learning using Consistency Regularization.- Towards Private and Fair Machine Learning: Group-Specific Differentially Private Stochastic Gradient Descent with Threshold Optimization.- LogMoE: Optimizing Mixture of Experts for Log Anomaly Detection via Knowledge Distillation.- Cross-Domain Few-Shot Learning with Equiangular Embedding and Dynamic Adversarial Augmentation.- ∞-Net: An Unsupervised Model for Online Graph Time-Series Denoising.- On Learnable Parameters of Optimal and Suboptimal Deep Learning Models.- Aero-engine Condition-Based Maintenance Planning Using Reinforcement Learning.- Multi-Timescale Processing with Heterogeneous Assembly Echo StateNetworks.- ADERec: Adaptive Data Augmentation Sequence Recommendation Based on Dual Network Architecture.- Pruning neural network parameters using recurrent neural networks.- MA-Mamba: Multi-Agent Reinforcement Learning with State Space Model.- Decentralized Extension for Centralized Multi-Agent Reinforcement Learning via Online Distillation.- Advancing RVFL networks: Robust classification with the HawkEye loss function.- An Enhanced MILP-based Verifier for Adversary Robustness of Neural Networks.- Hide-and-Seek GANs for Generation with Limited Data.- Unsupervised Robust Hypergraph Correlation Hashing for MultimediaRetrieval.- Emotional Atmosphere Soft Label for Emotion Recognition in Conversations.- CCATS: Moving Forward with Class-Conditional Time Series Generation.- M3ixTS: Mixing of Multi-patch and Multi-view For Time Series Forecasting.- CSTFormer: Cross Spatial-Temporal Learning Transformer withDynamic Sign Language Recognition through an Augmented Reality Environment.- MmFormer: A Novel Multi-Scale and Multi-Period Transformer Model for Irregular periodic Network Traffc Prediction.- Time Series Anomaly Detection via Temporal Dependencies and Multivariate Correlations Integrating.- Transformer-Based Long Time Series Forecasting with Decoupled Information Extraction and Information Complementarity.
