Zobrazeno 1 - 10
of 174
pro vyhledávání: '"Durand, Audrey"'
Autor:
Lefebvre, Randy, Durand, Audrey
Formulating a real-world problem under the Reinforcement Learning framework involves non-trivial design choices, such as selecting a discount factor for the learning objective (discounted cumulative rewards), which articulates the planning horizon of
Externí odkaz:
http://arxiv.org/abs/2407.15820
We focus on the online-based active learning (OAL) setting where an agent operates over a stream of observations and trades-off between the costly acquisition of information (labelled observations) and the cost of prediction errors. We propose a nove
Externí odkaz:
http://arxiv.org/abs/2405.08921
The partial monitoring (PM) framework provides a theoretical formulation of sequential learning problems with incomplete feedback. On each round, a learning agent plays an action while the environment simultaneously chooses an outcome. The agent then
Externí odkaz:
http://arxiv.org/abs/2402.05002
Association rule mining is one of the most studied research fields of data mining, with applications ranging from grocery basket problems to explainable classification systems. Classical association rule mining algorithms have several limitations, es
Externí odkaz:
http://arxiv.org/abs/2304.13717
Cancer treatment is an arduous process for patients and causes many side-effects during and post-treatment. The treatment can affect almost all body systems and result in pain, fatigue, sleep disturbances, cognitive impairments, etc. These conditions
Externí odkaz:
http://arxiv.org/abs/2302.09659
Polypharmacy, most often defined as the simultaneous consumption of five or more drugs at once, is a prevalent phenomenon in the older population. Some of these polypharmacies, deemed inappropriate, may be associated with adverse health outcomes such
Externí odkaz:
http://arxiv.org/abs/2212.05190
Association rule mining is one of the most studied research fields of data mining, with applications ranging from grocery basket problems to highly explainable classification systems. Classical association rule mining algorithms have several flaws es
Externí odkaz:
http://arxiv.org/abs/2211.12767
Autor:
Li, Tong, Nogas, Jacob, Song, Haochen, Kumar, Harsh, Durand, Audrey, Rafferty, Anna, Deliu, Nina, Villar, Sofia S., Williams, Joseph J.
Multi-armed bandit algorithms like Thompson Sampling (TS) can be used to conduct adaptive experiments, in which maximizing reward means that data is used to progressively assign participants to more effective arms. Such assignment strategies increase
Externí odkaz:
http://arxiv.org/abs/2112.08507
Autor:
Hitti, Yasmeen, Buzatu, Ionelia, Del Verme, Manuel, Lefsrud, Mark, Golemo, Florian, Durand, Audrey
Plants are dynamic systems that are integral to our existence and survival. Plants face environment changes and adapt over time to their surrounding conditions. We argue that plant responses to an environmental stimulus are a good example of a real-w
Externí odkaz:
http://arxiv.org/abs/2110.08307
Autor:
Hitti, Yasmeen, Buzatu, Ionelia, Verme, Manuel Del, Lefsrud, Mark, Golemo, Florian, Durand, Audrey
Publikováno v:
In Computers and Electronics in Agriculture February 2024 217