Name
Affiliation
Papers
LUIS CEZE
University of Washington, Seattle, WA, USA
129
Collaborators
Citations 
PageRank 
320
2183
125.93
Referers 
Referees 
References 
4387
3379
1708
Search Limit
1001000
Title
Citations
PageRank
Year
Robust Digital Molecular Design of Binarized Neural Networks.00.342021
Characterizing and Taming Resolution in Convolutional Neural Networks00.342021
Pure tensor program rewriting via access patterns (representation pearl)10.352021
Reticle: a virtual machine for programming modern FPGAs10.342021
VSS: A Storage System for Video Analytics00.342021
Genotype Extraction and False Relative Attacks: Security Risks to Third-Party Genetic Genealogy Services Beyond Identity Inference30.402020
Riptide - Fast End-to-End Binarized Neural Networks.00.342020
Automatic generation of high-performance quantized machine learning kernels.10.342020
LastLayer: Toward Hardware and Software Continuous Integration00.342020
VisualWorldDB - A DBMS for the Visual World.00.342020
PurpleDrop: A Digital Microfluidics-Based Platform for Hybrid Molecular-Electronics Applications00.342020
Scaling Microfluidics to Complex, Dynamic Protocols - Invited Paper.00.342019
DNA Data Storage and Near-Molecule Processing for the Yottabyte Era.00.342019
Vignette: Perceptual Compression for Video Storage and Processing Systems.00.342019
DNA Data Storage and Hybrid Molecular-Electronic Computing.10.432019
Puddle: A Dynamic, Error-Correcting, Full-Stack Microfluidics Platform10.402019
Synthesizing Number Generators for Stochastic Computing using Mixed Integer Programming.00.342019
Iterative Search for Reconfigurable Accelerator Blocks With a Compiler in the Loop00.342019
A Hardware–Software Blueprint for Flexible Deep Learning Specialization80.572019
A Taxonomy of General Purpose Approximate Computing Techniques.50.392018
Automating Generation of Low Precision Deep Learning Operators.00.342018
VTA: An Open Hardware-Software Stack for Deep Learning.10.352018
Leveraging the VTA-TVM Hardware-Software Stack for FPGA Acceleration of 8-bit ResNet-18 Inference.00.342018
MATIC: Learning around errors for efficient low-voltage neural network accelerators60.442018
Architecture Considerations for Stochastic Computing Accelerators.20.402018
Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training.120.532018
TVM: End-to-End Optimization Stack for Deep Learning.120.682018
Application Codesign of Near-Data Processing for Similarity Search10.412018
LightDB: a DBMS for virtual reality video10.352018
Learning to Optimize Tensor Programs.10.352018
Stochastic Synthesis for Stochastic Computing.00.342018
Customizing Progressive JPEG for Efficient Image Storage.00.342017
Exploring computation-communication tradeoffs in camera systems50.452017
Energy-Efficient Hybrid Stochastic-Binary Neural Networks for Near-Sensor Computing.130.802017
Computer Security, Privacy, And Dna Sequencing: Compromising Computers With Synthesized Dna, Privacy Leaks, And More10.432017
VisualCloud Demonstration: A DBMS for Virtual Reality.30.372017
Making data center computations fast, but not so furious.00.342017
IncBricks: Toward In-Network Computation with an In-Network Cache.190.782017
Clustering Billions of Reads for DNA Data Storage.00.342017
A hardware-friendly bilateral solver for real-time virtual reality video20.362017
A Visual Cloud for Virtual Reality Applications.00.342017
Democratizing Design for Future Computing Platforms.00.342017
Similarity Search on Automata Processors10.352017
Arch2030: A Vision of Computer Architecture Research over the Next 15 Years.00.342016
Approximate Computing: Unlocking Efficiency with Hardware-Software Co-Design.00.342016
Near Memory Similarity Search on Automata Processors.00.342016
Disciplined Inconsistency with Consistency Types.60.442016
NCAM: Near-Data Processing for Nearest Neighbor Search.00.342016
Optimizing synthesis with metasketches.210.782016
The 2014 Top Picks in Computer Architecture00.342015
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