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1.

Classical data structures that can outperform learned indexes (2018) (dawn.cs.stanford.edu)

252 points

5 years ago

2.

DAWN: Tools for AI and Data Product Development (dawn.cs.stanford.edu)

215 points

indescions_2017

8 years ago

3.

Classical Data Structures That Can Outperform Learned Indexes (dawn.cs.stanford.edu)

139 points

8 years ago

4.

HALP: High-Accuracy Low-Precision Training (dawn.cs.stanford.edu)

103 points

8 years ago

5.

Filter Before You Parse: Faster Analytics on Raw Data with Sparser (dawn.cs.stanford.edu)

86 points

8 years ago

6.

Implementing a Fast Research Compiler in Rust (dawn.cs.stanford.edu)

72 points

9 years ago

7.

Why Train What You Can Code? Rekall: A Compositional Approach to Video Analysis (dawn.cs.stanford.edu)

7 points

7 years ago

8.

Moment-based quantile sketches for efficient aggregation (dawn.cs.stanford.edu)

6 points

8 years ago

9.

Stanford DAWN Project (dawn.cs.stanford.edu)

6 points

9 years ago

10.

Classical Data Structures That Can Outperform Learned Indexes (dawn.cs.stanford.edu)

5 points

5 years ago

11.

New high score on GLUE mixes transfer learning/MTL/weak supervision/ensembling (dawn.cs.stanford.edu)

5 points

7 years ago

12.

Optimizing Data-Intensive Computations in Existing Libraries w/Split Annotations (dawn.cs.stanford.edu)

4 points

7 years ago

13.

DAWNBench v1 Deep Learning Benchmark Results (dawn.cs.stanford.edu)

4 points

8 years ago

14.

Willump: Statistical Optimizations for Fast ML Feature Computation (dawn.cs.stanford.edu)

3 points

6 years ago

15.

Moment-based quantile sketches for efficient aggregation (dawn.cs.stanford.edu)

3 points

8 years ago

16.

Stanford DAWN Deep Learning Benchmark (DAWNBench) (dawn.cs.stanford.edu)

3 points

8 years ago

17.

DAWNBench: An End-To-End Deep Learning Benchmark and Competition (dawn.cs.stanford.edu)

3 points

8 years ago

18.

Classical data structures that can outperform learned indexes (dawn.cs.stanford.edu)

2 points

2 years ago

19.

A Statistically-Aware End-to-End Optimizer for Machine Learning Inference (dawn.cs.stanford.edu)

2 points

7 years ago

20.

Model Assertions as a Tool for Quality Assurance and Improving ML Models (dawn.cs.stanford.edu)

2 points

7 years ago

21.

Moment-based quantile sketches for efficient aggregation (dawn.cs.stanford.edu)

2 points

8 years ago

22.

Earthquake Hunting with Efficient Time Series Similarity Search (dawn.cs.stanford.edu)

2 points

8 years ago

23.

Google TPU outperforms competition on ImageNet training performance benchmark (dawn.cs.stanford.edu)

2 points

8 years ago

24.

DAWNBench – Stanford Deep Learning Benchmark (dawn.cs.stanford.edu)

2 points

8 years ago

25.

Weak Supervision: The New Programming Paradigm for Machine Learning (dawn.cs.stanford.edu)

2 points

9 years ago

26.

Automatic Time Series Smoothing with ASAP – Stanford DAWN (dawn.cs.stanford.edu)

2 points

9 years ago

27.

Optimizing Data-Intensive Computations with Split Annotations (dawn.cs.stanford.edu)

1 point

7 years ago

28.

Moment-based quantile sketches for efficient aggregation (dawn.cs.stanford.edu)

1 point

8 years ago

29.

Moment-based quantile sketches for efficient aggregation (dawn.cs.stanford.edu)

1 point

8 years ago

30.

Moment-based quantile sketches for efficient aggregation (dawn.cs.stanford.edu)

1 point

8 years ago