TEST: Text prototype aligned embedding to activate LLM's ability for time series
This work summarizes two ways to accomplish Time-Series (TS) tasks in today's Large
Language Model (LLM) context: LLM-for-TS (model-centric) designs and trains a …
Language Model (LLM) context: LLM-for-TS (model-centric) designs and trains a …
SVP-T: a shape-level variable-position transformer for multivariate time series classification
Multivariate time series classification (MTSC), one of the most fundamental time series
applications, has not only gained substantial research attentions but has also emerged in …
applications, has not only gained substantial research attentions but has also emerged in …
Off-policy evaluation for human feedback
Off-policy evaluation (OPE) is important for closing the gap between offline training and
evaluation of reinforcement learning (RL), by estimating performance and/or rank of target …
evaluation of reinforcement learning (RL), by estimating performance and/or rank of target …
Bridging declarative, procedural, and conditional metacognitive knowledge gap using deep reinforcement learning
In deductive domains, three metacognitive knowledge types in ascending order are
declarative, procedural, and conditional learning. This work leverages Deep Reinforcement …
declarative, procedural, and conditional learning. This work leverages Deep Reinforcement …
Hope: Human-centric off-policy evaluation for e-learning and healthcare
Reinforcement learning (RL) has been extensively researched for enhancing human-
environment interactions in various human-centric tasks, including e-learning and …
environment interactions in various human-centric tasks, including e-learning and …
Offline learning of closed-loop deep brain stimulation controllers for parkinson disease treatment
Q Gao, SL Schmidt, A Chowdhury, G Feng… - Proceedings of the …, 2023 - dl.acm.org
Deep brain stimulation (DBS) has shown great promise toward treating motor symptoms
caused by Parkinson's disease (PD), by delivering electrical pulses to the Basal Ganglia …
caused by Parkinson's disease (PD), by delivering electrical pulses to the Basal Ganglia …
On trajectory augmentations for off-policy evaluation
In the realm of reinforcement learning (RL), off-policy evaluation (OPE) holds a pivotal
position, especially in high-stake human-involved scenarios such as e-learning and …
position, especially in high-stake human-involved scenarios such as e-learning and …
Graph-enabled reinforcement learning for time series forecasting with adaptive intelligence
Reinforcement learning (RL) is renowned for its proficiency in modeling sequential tasks
and adaptively learning latent data patterns. Deep learning models have been extensively …
and adaptively learning latent data patterns. Deep learning models have been extensively …
[PDF][PDF] Hierarchical Apprenticeship Learning for Disease Progression Modeling.
Disease progression modeling (DPM) plays an essential role in characterizing patients'
historical pathways and predicting their future risks. Apprenticeship learning (AL) aims to …
historical pathways and predicting their future risks. Apprenticeship learning (AL) aims to …
[PDF][PDF] Time-Series Data Imputation via Realistic Masking-Guided Tri-Attention Bi-GRU.
Time series data with missing values are ubiquitous in real applications due to various
unforeseen faults during data generation, storage, and transmission. Time-Series Data …
unforeseen faults during data generation, storage, and transmission. Time-Series Data …