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In this paper, we develop a new framework termed the sequential invariant information bottleneck (seq-IIB) to improve the generalization ability of learning ...
In this paper, we propose an extension of IRM to sequen- tial environment scenarios and develop a framework called sequential invariant information bottleneck ( ...
We propose a method to improve the accuracy of estimating robust invariant set by using a combination of sequential state updates and ... [Show full abstract] ...
Oct 12, 2021 · Abstract:Deep neural networks suffer from poor generalization to unseen environments when the underlying data distribution is different from ...
Jun 11, 2021 · Inspired by IRM, in this paper we propose a novel formulation for domain generalization, dubbed invariant information bottleneck (IIB). IIB aims ...
Missing: Sequential | Show results with:Sequential
A new neural network-based IB approach that dynamically drops spurious correlations and progressively selects the most task-relevant features across ...
We use a Variational Information Bottleneck (VIB) theory-based pruning approach to limit the information flow through the sequential cells of RNNs to a small ...
Sequential Invariant Information Bottleneck. Yichen ... In this paper, we develop a new framework termed the sequential invariant information bottleneck ...
Invariant Information Bottleneck for Domain Generalization
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Inspired by IRM, in this paper we propose a novel formulation for domain generalization, dubbed invariant information bottleneck (IIB). IIB aims at minimizing ...
Toledo, Venezian and Slonim revisit the sequential information information bottleneck (sIB) algorithm in contribution 9. Implementation aspects are ...