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Found 14 papers, 3 papers with code
The False Dawn: Reevaluating Google's Reinforcement Learning for Chip Macro Placement
Reinforcement learning (RL) for physical design of silicon chips in a Google 2021 Nature paper stirred controversy due to poorly documented claims that raised eyebrows and drew critical media coverage.
Scalable End-to-End ML Platforms: from AutoML to Self-serve
ML platforms help enable intelligent data-driven applications and maintain them with limited engineering effort.
Practical Knowledge Distillation: Using DNNs to Beat DNNs
While gradient boosting is known to outperform DNNs on tabular data, we close the gap for datasets with 100K+ rows and give DNNs an advantage on small data sets.
Looper: An end-to-end ML platform for product decisions
Modern software systems and products increasingly rely on machine learning models to make data-driven decisions based on interactions with users, infrastructure and other systems.
Text Ranking and Classification using Data Compression
A well-known but rarely used approach to text categorization uses conditional entropy estimates computed using data compression tools.
Regular Expressions for Fast-response COVID-19 Text Classification
For COVID-19, we build two sets of regular expressions: (1) for 66 languages, with 99% precision and recall >50%, (2) for the 11 most common languages, with precision >90% and recall >90%.
Prioritizing Original News on Facebook
This work outlines how we prioritize original news, a critical indicator of news quality.
Personalization for Web-based Services using Offline Reinforcement Learning
Large-scale Web-based services present opportunities for improving UI policies based on observed user interactions.
As Accurate as Needed, as Efficient as Possible: Approximations in DD-based Quantum Circuit Simulation
Quantum computers promise to solve important problems faster than conventional computers.
Quantum Physics
Just Like the Real Thing: Fast Weak Simulation of Quantum Computation
In this work, we focus on weak simulation that aims to produce outputs which are statistically indistinguishable from those of error-free quantum computers.
Quantum Physics
Quantum Supremacy Is Both Closer and Farther than It Appears
We simulate approximate sampling from the output of a circuit with 7x8 qubits and depth 1+40+1 by producing one million bitstring probabilities with fidelity 0. 5%, at an estimated cost of $35184.
Quantum Physics Distributed, Parallel, and Cluster Computing Emerging Technologies
A review of "Mem-computing NP-complete problems in polynomial time using polynomial resources" (arXiv:1411.4798)
The reviewed paper describes an analog device that empirically solves small instances of the NP-complete Subset Sum Problem (SSP).
Limits on Fundamental Limits to Computation
An indispensable part of our lives, computing has also become essential to industries and governments.
Emerging Technologies Quantum Physics
Constant-Optimized Quantum Circuits for Modular Multiplication and Exponentiation
Reversible circuits for modular multiplication $Cx$%$M$ with $x<M$ arise as components of modular exponentiation in Shor's quantum number-factoring algorithm.
Emerging Technologies Quantum Physics
