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01/31/2023
Preserving local densities in low-dimensional embeddings
Low-dimensional embeddings and visualizations are an indispensable tool ...
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10/05/2022
How Erdös and Rényi Win the Lottery
Random masks define surprisingly effective sparse neural network models,...
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10/05/2022
Dynamical Isometry for Residual Networks
The training success, training speed and generalization ability of neura...
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05/04/2022
Convolutional and Residual Networks Provably Contain Lottery Tickets
The Lottery Ticket Hypothesis continues to have a profound practical imp...
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05/04/2022
Most Activation Functions Can Win the Lottery Without Excessive Depth
The strong lottery ticket hypothesis has highlighted the potential for t...
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11/22/2021
Plant 'n' Seek: Can You Find the Winning Ticket?
The lottery ticket hypothesis has sparked the rapid development of pruni...
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11/22/2021
On the Existence of Universal Lottery Tickets
The lottery ticket hypothesis conjectures the existence of sparse subnet...
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10/21/2021
Towards strong pruning for lottery tickets with non-zero biases
The strong lottery ticket hypothesis holds the promise that pruning rand...
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07/06/2021
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification
Modeling the time evolution of discrete sets of items (e.g., genetic mut...
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09/09/2019
Cascade Size Distributions and Why They Matter
How likely is it that a few initial node activations are amplified to pr...
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06/17/2018
Exact information propagation through fully-connected feed forward neural networks
Neural network ensembles at initialisation give rise to the trainability...
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02/08/2018
Explicit size distributions of failure cascades redefine systemic risk on finite networks
How big is the risk that a few initial failures of nodes in a network am...
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12/05/2017