19 citations · 38 across the 11 of their papers we have counts for
8 papers
Beyond Statistical Learning: Exact Learning Is Essential for General Intelligence
András György, Tor Lattimore, Nevena Lazić +1
Sound deductive reasoning -- the ability to derive new knowledge from existing facts and rules -- is an indisputably desirable aspect of general intelligence. Despite the major adv…
A Second-Order Method for Stochastic Bandit Convex Optimisation
Tor Lattimore, András György
We introduce a simple and efficient algorithm for unconstrained zeroth-order stochastic convex bandits and prove its regret is at most $(1 + r/d)[d^{1.5} \sqrt{n} + d^3] polylog(n,…
Optimistic Meta-Gradients
Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue +3
We study the connection between gradient-based meta-learning and convex op-timisation. We observe that gradient descent with momentum is a special case of meta-gradients, and build…
A New Look at Dynamic Regret for Non-Stationary Stochastic Bandits
Yasin Abbasi-Yadkori, Andras Gyorgy, Nevena Lazic
We study the non-stationary stochastic multi-armed bandit problem, where the reward statistics of each arm may change several times during the course of learning. The performance o…
Perceptually Constrained Adversarial Attacks
Muhammad Zaid Hameed, Andras Gyorgy
Motivated by previous observations that the usually applied norms () do not capture the perceptual quality of adversarial examples in image classification, we p…
SDP Relaxation with Randomized Rounding for Energy Disaggregation
Kiarash Shaloudegi, András György, Csaba Szepesvári +1
We develop a scalable, computationally efficient method for the task of energy disaggregation for home appliance monitoring. In this problem the goal is to estimate the energy cons…