2 citations · 3 across the 11 of their papers we have counts for
6 papers · 1 filter
Using LLMs for Late Multimodal Sensor Fusion for Activity Recognition
Ilker Demirel, Karan Thakkar, Benjamin Elizalde +7
Sensor data streams provide valuable information around activities and context for downstream applications, though integrating complementary information can be challenging. We show…
Prediction-Powered Causal Inferences
Riccardo Cadei, Ilker Demirel, Piersilvio De Bartolomeis +4
In many scientific experiments, the data annotating cost constraints the pace for testing novel hypotheses. Yet, modern machine learning pipelines offer a promising solution, provi…
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang +40
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between…
Federated Multi-Armed Bandits Under Byzantine Attacks
Artun Saday, İlker Demirel, Yiğit Yıldırım +1
Multi-armed bandits (MAB) is a sequential decision-making model in which the learner controls the trade-off between exploration and exploitation to maximize its cumulative reward.…
Safe Linear Leveling Bandits
Ilker Demirel, Mehmet Ufuk Ozdemir, Cem Tekin
Multi-armed bandits (MAB) are extensively studied in various settings where the objective is to \textit{maximize} the actions' outcomes (i.e., rewards) over time. Since safety is c…
ESCADA: Efficient Safety and Context Aware Dose Allocation for Precision Medicine
Ilker Demirel, Ahmet Alparslan Celik, Cem Tekin
Finding an optimal individualized treatment regimen is considered one of the most challenging precision medicine problems. Various patient characteristics influence the response to…