7.7k citations
- California Institute of TechnologyUS534 papers
- Centre National de la Recherche ScientifiqueFR456 papers
- Massachusetts Institute of TechnologyUS357 papers
- Johns Hopkins UniversityUS333 papers
- Princeton UniversityUS328 papers
- University of Maryland, College ParkUS318 papers
- Fermi National Accelerator LaboratoryUS314 papers
- University of California, Los AngelesUS300 papers
- University of California San DiegoUS298 papers
- Imperial College LondonGB289 papers
- University of FloridaUS289 papers
- University of California, Santa BarbaraUS287 papers
124 papers · 1 filter
Seemo: A new tool for early design window view satisfaction evaluation in residential buildings
Jaeha Kim, Michael Kent, Katharina Kral +1
People spend approximately 90% of their lives indoors, and thus arguably, the indoor space design can significantly influence occupant well-being. Adequate views to the outside are…
Logic Shrinkage: Learned FPGA Netlist Sparsity for Efficient Neural Network Inference
Erwei Wang, James J. Davis, Georgios-Ilias Stavrou +3
FPGA-specific DNN architectures using the native LUTs as independently trainable inference operators have been shown to achieve favorable area-accuracy and energy-accuracy tradeoff…
Bayesian Optimization of Function Networks
Raul Astudillo, Peter I. Frazier
We consider Bayesian optimization of the output of a network of functions, where each function takes as input the output of its parent nodes, and where the network takes significan…
BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing
Tianfeng Liu, Yangrui Chen, Dan Li +7
Graph neural networks (GNNs) have extended the success of deep neural networks (DNNs) to non-Euclidean graph data, achieving ground-breaking performance on various tasks such as no…
Tree in Tree: from Decision Trees to Decision Graphs
Bingzhao Zhu, Mahsa Shoaran
Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree…
Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components
Nate Veldt, Austin R. Benson, Jon Kleinberg
Minimizing a sum of simple submodular functions of limited support is a special case of general submodular function minimization that has seen numerous applications in machine lear…