wackspurt

5 ms·

1.
by wackspurt 6y ago
My latest immersion into Beej's guide was through the GIOS course too! It also opened my eyes to the amount of familiarity/expertise my older co-workers had with systems programming (they helped me when when they heard me whining
2.
Detection and Classification of Acoustic Scenes and Events(DCASE) Challenge 2018(dcase.community)
1 points by wackspurt 8y ago|0 comments
3.
by wackspurt 8y ago
Relevant here: "Why don't I take military funding?" by Prof. Benjamin Kuipers. https://web.eecs.umich.edu/~kuipers/opinions/no-military-fun... From the introduction: """ Mostly it&#x2
4.
by wackspurt 8y ago
>>> becomes illegal if you say you're doing this to be intentionally subpoena-proof I didn't know that. Hmm...
5.
by wackspurt 8y ago
>>> We apply cutting edge machine learning techniques on petabytes of data and thousands of Spark/YARN nodes. I'm curious. Do you use an open-source Java ML library (dl4j, etc.) or do you have an in-house implementation?
6.
by wackspurt 8y ago
(Copy-pasting the message I already posted in this thread. Seems more relevant here) I think that adoption of privacy preserving data aggregation/analysis will become the norm. The most immediate applications are 1) telemetry data that
7.
by wackspurt 8y ago
I remember this paper on ad intelligence I read a few weeks ago: "Exploring ADINT: Using Ad Targeting for Surveillance on a Budget — or — How Alice Can Buy Ads to Track Bob". https://adint.cs.washington.edu/ADINT.p
8.
by wackspurt 8y ago
I think that adoption of privacy preserving data aggregation/analysis will become the norm. The most immediate applications are 1) telemetry data that is used for monitoring (for example, Google Chrome uses differential privacy for col
9.
by wackspurt 8y ago
That's funny. I wonder how human intrigues (and the literature/narratives around it) will be affected by ubiquitous computing and networking.
10.
by wackspurt 8y ago
Anomaly detection is performed at two levels: 1. A log key anomaly detection LSTM model (a type of recurrent neural network) predicts the next log message type (log key). If it is wrong for any log entry, the operator is alerted that there
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DeepLog: Anomaly Detection and Diagnosis from System Logs Through Deep Learning [pdf](cs.utah.edu)
5 points by wackspurt 8y ago|1 comments
12.
by wackspurt 8y ago
What you are describing sounds similar to a "quine". A quine is a non-empty computer program which takes no input and produces a copy of its own source code as its only output. https://en.wikipedia.org/wiki/Qu
13.
by wackspurt 8y ago
MacroBase's pipeline is broken up into the following operators: Transform, Classify, Explain. I find the Explanation operator very valuable and haven't seen something like this in any work in monitoring/anomaly detection (cor
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MacroBase: Prioritizing Attention in Fast Data(macrobase.stanford.edu)
67 points by wackspurt 8y ago|3 comments
15.
by wackspurt 8y ago
Based on my limited understanding* of differential privacy, it falls short on exactness (of aggregate values) and robustness (against malicious clients). I've lately been studying the literature on function secret sharing and I think i
16.
by wackspurt 8y ago
Can anyone here offer advice for doing anomaly detection in distributed systems? I'm not looking for advice on which models to use, per se. I'm more interested in how to go about things as a single-person team (building data wareh
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Learning to Reason with Neural Module Networks(bair.berkeley.edu)
2 points by wackspurt 9y ago|0 comments
18.
by wackspurt 9y ago
>> Other people do not expect this because there are papers about how to incentivize neurons to correspond to interesting features. Could you clarify that statement? Are you saying that it was unusual for this group to find such a neu
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by wackspurt 9y ago
Apparently, DP has some detractors. I was told by my signal processing professor that differential privacy wasn't really a solution for privacy preserving data analysis. He said something along these lines: "if I know something ab
20.
by wackspurt 9y ago
>>>Sentimental neuron sounds fascinating too. I didn't realize individual neurons could be talked about or understood outside of the concept of the NN. I am thinking in terms of "black box" its often referenced to in
21.
by wackspurt 9y ago
(Apologies for the slightly incoherent post below) I've been noticing a lot of work that digs into ML model internals (as they've done here to find the sentiment neuron) to understand why they work or use them to do something. Let
22.
by wackspurt 9y ago
Did you use something like Differential Privacy?
23.
by wackspurt 9y ago
"Each time you make a Voice Call on Telegram, a neural network learns from your and your device‘s feedback (naturally, it doesn’t have access to the contents of the conversation, it has only technical information such as network speed,
24.
by wackspurt 9y ago
Yes. That would be a story worth reading about because the octopus has a PhD!