Rationalizing constraints on the capacity for cognitive control

S Musslick, JD Cohen - Trends in Cognitive Sciences, 2021 - cell.com
Humans are remarkably limited in:(i) how many control-dependent tasks they can execute
simultaneously, and (ii) how intensely they can focus on a single task. These limitations are …

An integrative framework of conflict and control

D Becker, E Bijleveld, S Braem, K Fröber… - Trends in Cognitive …, 2024 - cell.com
People regularly encounter various types of conflict. Here, we ask if, and, if so, how, different
types of conflict, from lab-based Stroop conflicts to everyday-life self-control or moral …

A theory of learning to infer.

I Dasgupta, E Schulz, JB Tenenbaum… - Psychological …, 2020 - psycnet.apa.org
Bayesian theories of cognition assume that people can integrate probabilities rationally.
However, several empirical findings contradict this proposition: human probabilistic …

Efficiency of learning vs. processing: Towards a normative theory of multitasking

Y Sagiv, S Musslick, Y Niv, JD Cohen - arxiv preprint arxiv:2007.03124, 2020 - arxiv.org
A striking limitation of human cognition is our inability to execute some tasks simultaneously.
Recent work suggests that such limitations can arise from a fundamental tradeoff in network …

On the rational boundedness of cognitive control: Shared versus separated representations

One of the most fundamental and striking limitations of human cognition appears to be a
constraint in the number of control-dependent processes that can be executed at one time …

Resolution of the Erdős–Sauer problem on regular subgraphs

O Janzer, B Sudakov - Forum of Mathematics, Pi, 2023 - cambridge.org
In this paper, we completely resolve the well-known problem of Erdős and Sauer from 1975
which asks for the maximum number of edges an n-vertex graph can have without …

Topological limits to the parallel processing capability of network architectures

G Petri, S Musslick, B Dey, K Özcimder, D Turner… - Nature Physics, 2021 - nature.com
The ability to learn new tasks and generalize to others is a remarkable characteristic of both
human brains and recent artificial intelligence systems. The ability to perform multiple tasks …

Regular subgraphs at every density

D Chakraborti, O Janzer, A Methuku… - arxiv preprint arxiv …, 2024 - arxiv.org
In 1975, Erd\H {o} s and Sauer asked to estimate, for any constant $ r $, the maximum
number of edges an $ n $-vertex graph can have without containing an $ r $-regular …

Edge-disjoint cycles with the same vertex set

D Chakraborti, O Janzer, A Methuku… - arxiv preprint arxiv …, 2024 - arxiv.org
In 1975, Erd\H {o} s asked for the maximum number of edges that an $ n $-vertex graph can
have if it does not contain two edge-disjoint cycles on the same vertex set. It is known that …

Navigating the trade-off between multi-task learning and learning to multitask in deep neural networks

S Ravi, S Musslick, M Hamin, TL Willke… - arxiv preprint arxiv …, 2020 - arxiv.org
The terms multi-task learning and multitasking are easily confused. Multi-task learning refers
to a paradigm in machine learning in which a network is trained on various related tasks to …