Stochastic optimization problems involve making decisions in environments with uncertainty. This uncertainty can arise from various sources, such as sensor noise, system disturbances, or unpredictable external factors. It can real-time control and planning in robotics and autonomy, where computational efficiency is crucial for handling complex dynamics and cost functions in ever-changing environments. The core problem… →
Large language models (LLMs) have seen remarkable success in natural language processing (NLP). Large-scale deep learning models, especially transformer-based architectures, have grown exponentially in size and complexity, reaching billions to trillions of parameters. However, they pose major challenges in computational resources and memory usage. Even advanced GPUs struggle to handle models with trillions of parameters,… →
With the success of LLMs in various tasks, search engines have begun using generative methods to provide accurate answers with in-line citations to user queries. However, generating reliable and attributable answers, especially in open-ended information-seeking scenarios, poses challenges due to the complexity of questions and the broad scope of candidate-attributed answers. Existing methods typically focus… →
Automatic speech recognition (ASR) has become a crucial area in artificial intelligence, focusing on the ability to transcribe spoken language into text. ASR technology is widely used in various applications such as virtual assistants, real-time transcription, and voice-activated systems. These systems are integral to how users interact with technology, providing hands-free operation and improving accessibility.… →
In deep learning, neural network optimization has long been a crucial area of focus. Training large models like transformers and convolutional networks requires significant computational resources and time. Researchers have been exploring advanced optimization techniques to make this process more efficient. Traditionally, adaptive optimizers such as Adam have been used to speed training by adjusting… →
CONCLUSIONS: A CCTA-directed ICA strategy for patients with CABG is associated with expedition of the invasive procedure, and less fluoroscopy time, at the cost of higher total contrast volume and effective radiation dose, compared with the classic ICA approach. →
CONCLUSIONS: This proof-of-concept randomised controlled trial supports the feasibility and acceptability of the user co-facilitated psychoeducational programme for patients newly diagnosed with ADHD in an outpatient setting. While preliminary findings indicate promise in enhancing patient-reported outcomes, a larger study is warranted to assess the intervention’s effectiveness rigorously. →
CONCLUSIONS: Compared to the control group, levidex facilitated clinically relevant improvements in MS-related QoL, reduced sick days, and enhanced activity in PwMS over 6 months. These findings suggest that levidex can serve as an effective non-pharmacological adjunctive treatment element to standard care and could help improve QoL among PwMS. →
CONCLUSIONS: In the cohort of patients with moderate to severe IUA, the intrauterine estrogen-releasing system was more effective at reducing adhesion than traditional oral estrogen combined with an intrauterine Foley catheter after TCRA. This novel intrauterine system provides a new option for the management of IUA after surgery. →
This study aimed to investigate effects of epigallocatechin gallate (EGCG) on blood pressure (BP) and autonomic nervous system, indicated by 5-min heart rate variability (HRV) measurement in obese subjects, and determine correlations of BP with metabolic factors. In a double-blind, randomized controlled trial, obese subjects (n = 30) were randomly allocated to receive 150 mg… →