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Found 5 papers, 4 papers with code
Algorithm-assisted discovery of an intrinsic order among mathematical constants
In recent decades, a growing number of discoveries in fields of mathematics have been assisted by computer algorithms, primarily for exploring large parameter spaces that humans would take too long to investigate.
Fine-tuning giant neural networks on commodity hardware with automatic pipeline model parallelism
Fine-tuning is an increasingly common technique that leverages transfer learning to dramatically expedite the training of huge, high-quality models.
A Computational Approach to Packet Classification
To achieve high throughput and low latency, state-of-the-art algorithms strive to fit the rule lookup data structures into on-die caches; however, they do not scale well with the number of rules.
SpecFuzz: Bringing Spectre-type vulnerabilities to the surface
SpecFuzz is the first tool that enables dynamic testing for speculative execution vulnerabilities (e. g., Spectre).
Cryptography and Security
Faster Neural Network Training with Approximate Tensor Operations
We propose a novel technique for faster deep neural network training which systematically applies sample-based approximation to the constituent tensor operations, i. e., matrix multiplications and convolutions.
