Permutation search of tensor network structures via local sampling
Recent works put much effort into tensor network structure search (TN-SS), aiming to select
suitable tensor network (TN) structures, involving the TN-ranks, formats, and so on, for the …
suitable tensor network (TN) structures, involving the TN-ranks, formats, and so on, for the …
An online inference-aided incentive framework for information elicitation without verification
We study the design of incentive mechanisms for the problem of information elicitation
without verification (IEWV). In IEWV, a data requester seeks to design proper incentives to …
without verification (IEWV). In IEWV, a data requester seeks to design proper incentives to …
Online algorithms for hierarchical inference in deep learning applications at the edge
We consider a resource-constrained Edge Device (ED), such as an IoT sensor or a
microcontroller unit, embedded with a small-size ML model (S-ML) for a generic …
microcontroller unit, embedded with a small-size ML model (S-ML) for a generic …
Getting the Best Out of Both Worlds: Algorithms for Hierarchical Inference at the Edge
VN Moothedath, JP Champati… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
We consider a resource-constrained Edge Device (ED), such as an IoT sensor or a
microcontroller unit, embedded with a small-size ML model (S-ML) for a generic …
microcontroller unit, embedded with a small-size ML model (S-ML) for a generic …
Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm
The supplement is divided into four parts. Supplementary Material A contains the proofs of
Theorems 2, 3, and 5, and Propositions 1 and 2. Supplementary Material B gives the proofs …
Theorems 2, 3, and 5, and Propositions 1 and 2. Supplementary Material B gives the proofs …
A bayesian approach for stochastic continuum-armed bandit with long-term constraints
Z Shi, A Eryilmaz - International Conference on Artificial …, 2022 - proceedings.mlr.press
Despite many valuable advances in the domain of online convex optimization over the last
decade, many machine learning and networking problems of interest do not fit into that …
decade, many machine learning and networking problems of interest do not fit into that …
Adaptation to Misspecified Kernel Regularity in Kernelised Bandits
In continuum-armed bandit problems where the underlying function resides in a reproducing
kernel Hilbert space (RKHS), namely, the kernelised bandit problems, an important open …
kernel Hilbert space (RKHS), namely, the kernelised bandit problems, an important open …
Instance dependent regret analysis of kernelized bandits
S Shekhar, T Javidi - International Conference on Machine …, 2022 - proceedings.mlr.press
We study the problem of designing an adaptive strategy for querying a noisy zeroth-order-
oracle to efficiently learn about the optimizer of an unknown function $ f $. To make the …
oracle to efficiently learn about the optimizer of an unknown function $ f $. To make the …
[PDF][PDF] Adaptation to Misspecified Kernel Regularization in Kernelised Bandits
Y Liu, A Singh - Proceedings of the International Workshop on Artificial …, 2023 - par.nsf.gov
In continuum-armed bandit problems where the underlying function resides in a reproducing
kernel Hilbert space (RKHS), namely, the kernelised bandit problems, an important open …
kernel Hilbert space (RKHS), namely, the kernelised bandit problems, an important open …
Topics in Statistical Machine Learning
H Pu - 2022 - search.proquest.com
Modern statistical machine learning combines statistics with the computational sciences
including computer science and optimization. The research in statistical machine learning …
including computer science and optimization. The research in statistical machine learning …