Y
HN Search
Hacker News Search
new
|
comments
|
top
|
jobs
conductrics
searching PlanetScale…
1.
▲
2.
▲
3.
▲
4.
▲
5.
▲
6.
▲
10 ms
·
31.
▲
The Multi-Armed Bandit (MAB) problem and the opportunity costs of A/B Testing
(conductrics.com)
4 points
by
conductrics
14y ago
|
0 comments
32.
▲
List of Machine Learning and Data Science Resources - Part 2
(conductrics.com)
46 points
by
conductrics
14y ago
|
1 comments
33.
▲
by
conductrics
14y ago
I reached out to Yann LeCun and he emailed me a couple more recent links. I updated the deep learning section of the post to include them. Feel free to check them out.
34.
▲
by
conductrics
14y ago
Thanks! Sure, I didn't mean to imply that once you learn Linear Algebra you are all done - just that it you really need it and will make your life much easier once you do. Yeah, I didn't include a ton of stuff - nothing on EM, trees, boosti
35.
▲
Adaptive A/B Testing - More on Bandits
(conductrics.com)
1 points
by
conductrics
14y ago
|
0 comments
36.
▲
by
conductrics
14y ago
Huh, looks like all of the companies are out of NY and mostly fashion related. Its too bad it was more of a PR piece for these companies, rather than a deeper look at gender and class.
37.
▲
Nurturing a baby and a start-up business
(nytimes.com)
10 points
by
conductrics
14y ago
|
1 comments
38.
▲
by
conductrics
14y ago
Disclaimer: I also have software for running AB/MVT as well as adaptive control problems (so bandits as well as extended sequential decisions) at www.conductrics.com. I wouldn't sweat too much UCB methods vs e-greedy or other heuristics for
39.
▲
by
conductrics
14y ago
This is a good coversation. So the Disclaimer, my company Conductrics.com allows you to use algos similar to bandits as well as AB/MVT. AB can be thought of as more of a form of epoch- greedy - you play uniform random then play greedy. One
40.
▲
by
conductrics
14y ago
Is that true in the e-greedy case? Sure, during the exploit call, they are not independent, but during the explore portion I would assume they are, since they have been randomly assigned into the exploration pool (epsilon) and then drawn f
41.
▲
by
conductrics
14y ago
Of course, of the environment is truely stationary, then the easiest simpest hack method for exploration is just seed the initial values for each option (A/B../Z) with a an optimistic guess (so something you know is higher than the true val
42.
▲
by
conductrics
14y ago
You might want to look at botlzman/softmax if you want to weight the prob of selection as a function of the current estimated value. One tricky bit is figuring out a good setting for the temperature parameter. Another poster alluded to sof
43.
▲
by
conductrics
14y ago
A GA is a zeroth order optimization method. A Bandit is a type of decision problem. So, bandit is a single state RL problem were one is trying to make decisions in an environment in order to min regret. GA is a general optimization approach
44.
▲
by
conductrics
14y ago
Well I guess you could be running a MANOVA or something to test over joint outcomes, but the AB test is over some sort of metric. I mean, when you set up an experiment, you need to have defined the dependent variable first. Now, after you
45.
▲
by
conductrics
14y ago
I think rather than get hung up on e-greedy vs. A/B testing vs UCB (Bayesian vs. non Bayesian), it is helpful to first step back and think about the larger problem of online learning as a form of the prediction/control problem. The joint pr
46.
▲
by
conductrics
14y ago
Actually, you kind of are already in the RL space when using AB testing to make online decisions, you just may not be thinking of it that way. From Sutton & Barto "Reinforcement learning is learning what to do--how to map situations to
47.
▲
by
conductrics
14y ago
If you are using an epsilon-greedy approach (or something similar), then I believe that the data collected during the exploration portion - (the random calls) are open, albeit with less power due to reduced sample size, to standard hypothes
48.
▲
by
conductrics
14y ago
This is part of a larger class of problems known as reinforcement learning problems. A/B testing when used for decision optimization can be thought of (sort of) as just a form of bandit using an epsilon-first approach. You play random until
49.
▲
by
conductrics
15y ago
I put this together - feel free to give any feedback.
50.
▲
Nest Thermostat: Keeping Tabs along with the Temp
(mgershoff.wordpress.com)
1 points
by
conductrics
15y ago
|
0 comments
51.
▲
by
conductrics
15y ago
Other than how it affects your chance of success, this seems a little silly. #1 #2 .. who cares? Why get all tribal about your city? There are tons of industries here in NYC, so if you are targeting your offering to larger businesses, then
52.
▲
Intelligent Agents for Analytics
(mgershoff.wordpress.com)
2 points
by
conductrics
15y ago
|
0 comments
53.
▲
by
conductrics
15y ago
When I am trying a new whisky or brandy, I like to have a pour of something I know, so I have a reference point. I have found that time of day, outside temperature, what I am eating or have eaten, etc. really affects how much I am enjoying
54.
▲
by
conductrics
15y ago
Not sure why the focusing on the learning alogs or the utility of the thermostat - my guess is that company really isn't about the thermostat at all. You can almost hear the founders/investors excitedly throwing around the various buzz ter
55.
▲
by
conductrics
15y ago
My wife is a scotch expert. She hosts tastings where they taste scotch of three different ages. It used to be that after the tasting, most people would rate the oldest one the best. She then started to do blind tastings (tasters didn't kn
56.
▲
by
conductrics
15y ago
To get grounded in AI buy Russell and Norvig's AI text http://aima.cs.berkeley.edu/ They also cover Bayes Nets - btw just remember that at its heart, the Bayes Net is just a compact way to write/represent a joint distribution. Good Luck
57.
▲
Facebook-Led Consortium Plans to Remake Big Computing
(bits.blogs.nytimes.com)
3 points
by
conductrics
15y ago
|
0 comments
58.
▲
Quantum Chocolate Boxes
(rjlipton.wordpress.com)
2 points
by
conductrics
15y ago
|
0 comments
59.
▲
Stephen Boyd: Distributed Optimization and Statistics via ADMM [pdf]
(stanford.edu)
2 points
by
conductrics
15y ago
|
0 comments
60.
▲
by
conductrics
15y ago
I guess it all depends on one's discount rate. Now that I am older I wish I had taken a few more 'waste of time' classes - esp in the arts.
More ›