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Found 8 papers, 3 papers with code
Optimal Response Initiation: Why Recent Experience Matters
We propose a rationally motivated mathematical model of this sequential adaptation of control, based on a diffusion model of the decision process in which difficulty corresponds to the drift rate for the correct response.
Sequential effects reflect parallel learning of multiple environmental regularities
The Dynamic Belief Model (DBM) (Yu & Cohen, 2008) explains sequential effects in 2AFC tasks as a rational consequence of a dynamic internal representation that tracks second-order statistics of the trial sequence (repetition rates) and predicts whether the upcoming trial will be a repetition or an alternation of the previous trial.
Improving Human Judgments by Decontaminating Sequential Dependencies
Our decontamination techniques yield an over 20% reduction in the error of human judgments.
Reinforcement Learning with Analogical Similarity to Guide Schema Induction and Attention
Research in analogical reasoning suggests that higher-order cognitive functions such as abstract reasoning, far transfer, and creativity are founded on recognizing structural similarities among relational systems.
Robust priors for regularized regression
We successfully applied this approach to a number of decision and classification problems, as well as analyzing simulated brain imaging data.
Low-rank extended Kalman filtering for online learning of neural networks from streaming data
We propose an efficient online approximate Bayesian inference algorithm for estimating the parameters of a nonlinear function from a potentially non-stationary data stream.
Noise misleads rotation invariant algorithms on sparse targets
It is well known that the class of rotation invariant algorithms are suboptimal even for learning sparse linear problems when the number of examples is below the "dimension" of the problem.
Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training
We explore the training dynamics of neural networks in a structured non-IID setting where documents are presented cyclically in a fixed, repeated sequence.
