Daniel Kang

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Challenges and Opportunities in DNN-Based Video Analytics: A Demo of the BlazeIt Video Query Engine
Daniel Kang, Peter Bailis, Matei Zaharia
CIDR 2019

Model Assertions for Debugging Machine Learning
Daniel Kang*, Deepti Raghavan*, Peter Bailis, Matei Zaharia
NeurIPS MLSys Workshop 2018, Contributed Talk

Analysis of the Time-To-Accuracy Metric and Entries in the DAWNBench Deep Learning Benchmark
Cody Coleman*, Deepak Narayanan*, Daniel Kang*, Tian Zhao, Jian Zhang, Luigi Nardi, Peter Bailis, Kunle Olukotun, Chris Ré, and Matei Zaharia
NeurIPS MLSys Workshop 2018

Block-wise Intermediate Representation Training for Model Compression
Animesh Koratana*, Daniel Kang*, Peter Bailis, Matei Zaharia
NeurIPS CDNNRIA Workshop 2018

NoScope: Optimizing Neural Network Queries over Video at Scale
Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia
PVLDB 2017

BlazeIt: An Optimizing Query Engine for Video at Scale
Daniel Kang, Peter Bailis, Matei Zaharia
SysML 2018

DAWNBench: An End-to-End Deep Learning Benchmark and Competition
Cody Coleman, Deepak Narayanan, Daniel Kang, Tian Zhao, Jian Zhang, Luigi Nardi, Peter Bailis, Kunle Olukotun, Chris Ré, and Matei Zaharia
NIPS ML Systems Workshop 2017, Contributed Talk

A synergistic DNA logic predicts genome-wide chromatin accessibility
Tatsunori Hashimoto*, Richard I. Sherwood*, Daniel Kang*, Nisha Rajagopal, Amira Barkal, Haoyang Zeng, Bart Emons, Sharanya Srinivasan, Tommi Jaakkola, David Gifford
Genome Research (2016)

GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding
Haoyang Zeng, Tatsunori Hashimoto, Daniel Kang, David Gifford
Bioinformatics (2016)

Non-trapping surfaces of revolution with long-living resonances
Kiril Datchev, Daniel Kang, Andre Kessler
Mathematical Research Letters (2015)