Algorithmic Transparency with Strategic Users
Should firms that apply machine learning algorithms in their decision making make their algorithms transparent to the users they affect? Despite the growing calls for algorithmic transparency, most…
A Survey on Evolutionary Constrained Multiobjective Optimization
Handling constrained multiobjective optimization problems (CMOPs) is extremely challenging, since multiple conflicting objectives subject to various constraints require to be simultaneously optimiz…
A Biomimetic Optical Skin for Multimodal Tactile Perception Based on Optical …
Tactile sensation is one of the critical ways humans perceive the world and is fundamental for the interaction with the surroundings. The development of haptic sensors can enable us to extend and t…
Flexible Wearable Optical Sensor Based on Optical Microfiber Bragg Grating
Wearable sensing devices, which can find tremendous applications in healthcare and automation, are attracting great attention in recent years. Herein, we report a flexible wearable optical sensor (…
Analysis and Design of a High Transmittivity and Narrowband Tunable Lithium N…
Tunable Fabry-Perot (FP) filters are being increasingly employed in tunable fiber lasers for wavelength selection and tuning. To address single cavity restrictions on transmittivity and achieve nar…
BenchENAS : A Benchmarking Platform for Evolutionary Neural Architecture Search
Neural architecture search (NAS), which automatically designs the architectures of deep neural networks, has achieved breakthrough success over many applications in the past few years. Among differ…
Cascaded Algorithm Selection With Extreme-Region UCB Bandit
AutoML aims at best configuring learning systems automatically. It contains core subtasks of algorithm selection and hyper-parameter tuning. Previous approaches considered searching in the joint hy…
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation…
We develop provably efficient reinforcement learning algorithms for two-player zero-sum finite-horizon Markov games with simultaneous moves. To incorporate function approximation, we consider a fam…
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation…
We develop provably efficient reinforcement learning algorithms for two-player zero-sum finite-horizon Markov games with simultaneous moves. To incorporate function approximation, we consider a fam…
Plasmonic Gold Nanostar Mediated Self-Photothermal Modulation of Microfiber B…
Photothermal actuation that leverages optical fiber and plasmonic materials would not only add a practical function but also spur many important applications for the fiber-optic sensors, for exampl…
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