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CO-OptimalTransport

Neural Information Processing Systems

When one models the considered sets of samples as empirical probability distributions, Optimal Transport (OT)frameworkprovides asolution tofind,without supervision, asoft-correspondence mapbetweenthemgivenbyan optimalcoupling.



a284df1155ec3e67286080500df36a9a-Paper.pdf

Neural Information Processing Systems

Recent approaches include priors on the feature attribution of a deep neural network (DNN) into the training process to reduce the dependence on unwanted features. However, until now one needed to trade off high-quality attributions, satisfying desirable axioms, against the time required to compute them. This in turn either led to long training times or ineffective attribution priors.




Telstra joint venture to axe more than 200 jobs amid AI rollout

The Guardian

Telstra CEO Vicki Brady will oversee 209 job cuts, as the telco rolls out AI capabilities and sends some jobs offshore. It comes after a $700m joint venture in 2025 with technology consultancy Accenture. Telstra CEO Vicki Brady will oversee 209 job cuts, as the telco rolls out AI capabilities and sends some jobs offshore. It comes after a $700m joint venture in 2025 with technology consultancy Accenture. Some jobs will be moved offshore in wake of telco's $700m partnership with tech consultancy Accenture More than 200 Telstra jobs are expected to be cut, as the telco rolls out AI capabilities and sends some jobs to India.


Task-levelDifferentiallyPrivateMetaLearning

Neural Information Processing Systems

Specifically, meta learning takes in a collection of tasks (datasets) sampled from an unknown distribution. Each task defines a learning problem with respect to an input dataset.