64 citations · 253 across the 34 of their papers we have counts for
8 papers · 1 filter
Preference-Based Batch and Sequential Teaching
Farnam Mansouri, Yuxin Chen, Ara Vartanian +2
Algorithmic machine teaching studies the interaction between a teacher and a learner where the teacher selects labeled examples aiming at teaching a target hypothesis. In a quest t…
The Teaching Dimension of Kernel Perceptron
Akash Kumar, Hanqi Zhang, Adish Singla +1
Algorithmic machine teaching has been studied under the linear setting where exact teaching is possible. However, little is known for teaching nonlinear learners. Here, we establis…
Using Ensemble Classifiers to Detect Incipient Anomalies
Baihong Jin, Yingshui Tan, Albert Liu +3
Incipient anomalies present milder symptoms compared to severe ones, and are more difficult to detect and diagnose due to their close resemblance to normal operating conditions. Th…
Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI
Yingshui Tan, Baihong Jin, Xiangyu Yue +2
Ensemble learning is widely applied in Machine Learning (ML) to improve model performance and to mitigate decision risks. In this approach, predictions from a diverse set of learne…
Are Ensemble Classifiers Powerful Enough for the Detection and Diagnosis of Intermediate-Severity Faults?
Baihong Jin, Yingshui Tan, Yuxin Chen +2
Intermediate-Severity (IS) faults present milder symptoms compared to severe faults, and are more difficult to detect and diagnose due to their close resemblance to normal operatin…
Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries
Akash Kumar, Adish Singla, Yisong Yue +1
We examine the task of locating a target region among those induced by intersections of halfspaces in . This generic task connects to fundamental machine learning…
An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles
Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
Energy-efficient navigation constitutes an important challenge in electric vehicles, due to their limited battery capacity. We employ a Bayesian approach to model the energy consum…
Adaptive Teaching of Temporal Logic Formulas to Learners with Preferences
Zhe Xu, Yuxin Chen, Ufuk Topcu
Machine teaching is an algorithmic framework for teaching a target hypothesis via a sequence of examples or demonstrations. We investigate machine teaching for temporal logic formu…