Practice Management

Staffing & Scheduling

Latest AI and machine learning research in staffing & scheduling for healthcare professionals.

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The Estimation of Continual Causal Effect for Dataset Shifting Streams

Causal effect estimation has been widely used in marketing optimization. The framework of an uplif...

Memento: Augmenting Personalized Memory via Practical Multimodal Wearable Sensing in Visual Search and Wayfinding Navigation

Working memory involves the temporary retention of information over short periods. It is a critica...

Bullet: Boosting GPU Utilization for LLM Serving via Dynamic Spatial-Temporal Orchestration

Modern LLM serving systems confront inefficient GPU utilization due to the fundamental mismatch be...

Keep the General, Inject the Specific: Structured Dialogue Fine-Tuning for Knowledge Injection without Catastrophic Forgetting

Large Vision Language Models have demonstrated impressive versatile capabilities through extensive...

Swapped Logit Distillation via Bi-level Teacher Alignment

Knowledge distillation (KD) compresses the network capacity by transferring knowledge from a large...

DiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning

Explainable artificial intelligence (XAI) has become increasingly important in decision-critical d...

TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning

For deep learning-based image steganography frameworks, in order to ensure the invisibility and re...

STCL:Curriculum learning Strategies for deep learning image steganography models

Aiming at the problems of poor quality of steganographic images and slow network convergence of im...

DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training

Although large language models (LLMs) have recently achieved remarkable performance on various com...

OptimAI: Optimization from Natural Language Using LLM-Powered AI Agents

Optimization plays a vital role in scientific research and practical applications. However, formul...

Decoupled Global-Local Alignment for Improving Compositional Understanding

Contrastive Language-Image Pre-training (CLIP) has achieved success on multiple downstream tasks b...

Rethinking Generalizable Infrared Small Target Detection: A Real-scene Benchmark and Cross-view Representation Learning

Infrared small target detection (ISTD) is highly sensitive to sensor type, observation conditions,...

Deep, data-driven modeling of room acoustics: literature review and research perspectives

Our everyday auditory experience is shaped by the acoustics of the indoor environments in which we...

Split-quaternions for perceptual white balance

We propose a perceptual chromatic adaptation transform for white balance that makes use of split-q...

Advancing Embodied Intelligence in Robotic-Assisted Endovascular Procedures: A Systematic Review of AI Solutions

Endovascular procedures have revolutionized the treatment of vascular diseases thanks to minimally...

PPO-EPO: Energy and Performance Optimization for O-RAN Using Reinforcement Learning

Energy consumption in mobile communication networks has become a significant challenge due to its ...

Entropic Time Schedulers for Generative Diffusion Models

The practical performance of generative diffusion models depends on the appropriate choice of the ...

Bayesian continual learning and forgetting in neural networks

Biological synapses effortlessly balance memory retention and flexibility, yet artificial neural n...

GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs

Large Language Models (LLMs) trained on extensive datasets often learn sensitive information, whic...

Boosting Reservoir Computing with Brain-inspired Adaptive Dynamics

Reservoir computers (RCs) provide a computationally efficient alternative to deep learning while a...

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