Equilibrium Propagation (EP) is a learning algorithm that applies to Energy-Based Models (EBMs) on static inputs. It estimates loss gradients by contrasting two steady states of the same EBM, rather than resorting to explicit adjoint dynamics. EP originally appealed as a plausible learning theory for biological subst...
G. Pourcel, Debabrota Basu, Maxence Ernoult et al.· Neuromorphic Computing and E...· 0 citations
Over the past decade, Machine Learning (ML) has been trained under dual objectives: minimizing prediction error via Empirical Risk Minimization (ERM) while controlling unfairness bias. In practice, however, fairness-aware training often yields limited improvements over standard ERM, making reliable post hoc auditing es...
This paper revisit the nuances of long-term fairness achievable by an ADM-- specifically, through the lens of a loan approver inducing a population-level wealth dynamics, by developing Eutopia: a lending-process simulator enabled with a novel performative data generator to learn long-term fair strategies.
V. Palit, Udvas Das, Brahim Driss et al.· arXiv.org· 0 citations
This work revisits the regret lower and upper bounds of ϵ -global DP bandits and proves a tighter regret lower bound involving a novel information-theoretic quantity characterising the hardness of ϵ -global DP in stochastic bandits.
Achraf Azize, Yulian Wu, Junya Honda et al.· Neural Information Processin...· 0 citations
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