15 citations · 79 across the 26 of their papers we have counts for
6 papers · 1 filter
Online Semi-Supervised Learning in Contextual Bandits with Episodic Reward
Baihan Lin
We considered a novel practical problem of online learning with episodically revealed rewards, motivated by several real-world applications, where the contexts are nonstationary ov…
Predicting human decision making in psychological tasks with recurrent neural networks
Baihan Lin, Djallel Bouneffouf, Guillermo Cecchi
Unlike traditional time series, the action sequences of human decision making usually involve many cognitive processes such as beliefs, desires, intentions, and theory of mind, i.e…
Online Learning in Iterated Prisoner's Dilemma to Mimic Human Behavior
Baihan Lin, Djallel Bouneffouf, Guillermo Cecchi
As an important psychological and social experiment, the Iterated Prisoner's Dilemma (IPD) treats the choice to cooperate or defect as an atomic action. We propose to study the beh…
Speaker Diarization as a Fully Online Learning Problem in MiniVox
Baihan Lin, Xinxin Zhang
We proposed a novel machine learning framework to conduct real-time multi-speaker diarization and recognition without prior registration and pretraining in a fully online learning…
Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL
Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf +2
Artificial behavioral agents are often evaluated based on their consistent behaviors and performance to take sequential actions in an environment to maximize some notion of cumulat…
Keep It Real: a Window to Real Reality in Virtual Reality
Baihan Lin
This paper proposed a new interaction paradigm in the virtual reality (VR) environments, which consists of a virtual mirror or window projected onto a virtual surface, representing…