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--- distributed_ml [2018/03/14 22:18]
patra
+++ distributed_ml [2018/04/10 14:36]
damaskin
@@ Line 4: / Line 4: @@
 === Asynchronous ML on android devices===
-This project is related to training ML algorithms asynchronously on Android devices. The challenges here are primarily: mobile churn, latency, memory, bandwidth and accuracy. The main goal is building a framework to address these challenges.
+This project is related to training ML algorithms asynchronously on Android devices. The challenges here are primarily: mobile churn, latency, energy consumption, memory, bandwidth and accuracy.
 Related papers:\\
 [1] __[[http://ttic.uchicago.edu/~kgimpel/papers/gimpel+das+smith.conll10.pdf|Distributed Asynchronous Online Learning for Natural Language Processing]]__ \\
-[2] __[[http://net.pku.edu.cn/~cuibin/Papers/2017%20sigmod.pdf|Heterogeneity-aware Distributed Parameter Servers]]__
+[2] __[[http://net.pku.edu.cn/~cuibin/Papers/2017%20sigmod.pdf|Heterogeneity-aware Distributed Parameter Servers]]__ \\
+[3] __[[http://proceedings.mlr.press/v70/zhang17e.html|ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning]]__
 === Multi-output multi-class classification ===
@@ Line 45: / Line 47: @@
 [2] __[[http://www.vldb.org/pvldb/vol9/p1695-upadhyaya.pdf|Price-Optimal Querying with Data APIs]]__\\
 [3] __[[http://pages.cs.wisc.edu/~paris/papers/data_pricing.pdf|Query-Based Data Pricing]]__\\
+===Black-Box Attacks against Recommender Systems===
+A recommender system can be viewed as a black-box that users query with feedback (e.g., ratings, clicks) before getting the output list of recommendations.
+The goal is to infer properties of the recommendation algorithm by observing the output from different queries.
+Related papers:\\
+[1] __[[https://www.usenix.org/system/files/conference/usenixsecurity16/sec16_paper_tramer.pdf|Stealing Machine Learning Models via Prediction APIs]]__\\
+[2] __[[https://arxiv.org/pdf/1602.02697v3.pdf|Practical Black-Box Attacks against Deep Learning Systems using Adversarial Examples]]__\\
 **Contact:** __[[http://people.epfl.ch/georgios.damaskinos|Georgios Damaskinos]]__