“Amazon”
By Decision of the European Court of Justice 11 July 2013 – Ca C-52111. 2013
Subfields: Recommender Systems
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Recommender Systems
- Mário Almeida
- Nicholas Donald Lane
- Karthik Narasimhan
- Nate Kushman
- Regina Barzilay
- Stylianos I. Venieris
- Ilias Leontiadis
- Eduardo DeLeon
Citations in the corpus
- Spanner: Google's Globally-Distributed Database (2012, unknown): “Consistent replication across datacenters as a storage service has been provided by Megastore [5] and Dy-namoDB [3].”
- Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge (2016, methodology): “In this step, Mechanical Turk (Amazon, 2003) human workers paraphrase the generated synthetic descrip-Table NL-RX Using the procedure described above, we create a new public dataset (NL-RX) comprising of 10,000 regular expressions and their corresponding natural language descriptions.”
- Blended Latent Diffusion (2022, unknown): “In addition, we conducted a user study on Amazon Mechanical Turk (AMT) [Amazon 2022] to assess the visual quality and text-matching of our results.”
- Azure Accelerated Networking: SmartNICs in the Public Cloud (2018, background): “The public cloud is the backbone behind a massive and rapidly growing percentage of online software services [1, 2, 3].”
- Estimating the Causal Impact of Recommendation Systems from Observational Data (2015, background): “Moreover, because such correlations are likely to be common—indeed, systems such as Amazon’s “Customers who bought this also bought” [Linden et al. 2003] rely on them to generate their recommendations—the overestimate is potentially large.”
- SPINN: synergistic progressive inference of neural networks over device and cloud (2020, methodology): “With this setup, inputs collected by mobile devices are transmitted to a remote server to perform CNN inference using powerful accelerators [3, 6, 12, 19, 31, 32].”
- Fault Analysis and Debugging of Microservice Systems: Industrial Survey, Benchmark System, and Empirical Study (2018, background): “Synchronous invocations are considered harmful due to the multiplicative effect of downtime [9].”