Europe
Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning
Rui Luo, Jianhong Wang, Yaodong Yang, Jun WANG, Zhanxing Zhu
Neural Information Processing Systems http://nips.cc/
Multi-Agent First Order Constrained Optimization in Policy Space
In the realm of multi-agent reinforcement learning (MARL), achieving high performance is crucial for a successful multi-agent system.
NeuralFuse: Learning to Recover the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes Hao-Lun Sun
Energy-efficient computing is of primary importance to the effective deployment of deep neural networks (DNNs), particularly in edge devices and in on-chip AI systems. Increasing DNN computation's energy efficiency and lowering its carbon footprint require iterative efforts from both chip designers and algorithm developers.
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds
Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao
Empirical results, however,suggest thatnetworks of moderate size already yield appealing performance. To explain such a gap, a common belief is that many data sets exhibit low dimensional structures, and can be modeled as samples near a low dimensional manifold.
EgoChoir: Capturing 3D H uman-O bject Interaction Regions from Egocentric Views Y uhang Y ang
For the egocentric HOI, in addition to perceiving semantics e.g., "what" interaction is occurring, capturing "where" the interaction specifically manifests in 3D space is
SEGA: Variance Reduction via Gradient Sketching
Filip Hanzely, Konstantin Mishchenko, Peter Richtarik
Neural Information Processing Systems http://nips.cc/
Unsupervised Meta-Learning for Few-Shot Image Classification
Siavash Khodadadeh, Ladislau Boloni, Mubarak Shah
Neural Information Processing Systems http://nips.cc/