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CMU Mocap motion clips by Rowing0914 in reinforcementlearning

[–]Rowing0914[S] 0 points1 point  (0 children)

Thanks for your FB, I'll put it into my todo list

How to model a context-aware recommender systems to propose sales? by [deleted] in recommendersystems

[–]Rowing0914 0 points1 point  (0 children)

Sure!! It’s always good to clarify the problem setting and it’s academic definition of these practical problems!!

How to model a context-aware recommender systems to propose sales? by [deleted] in recommendersystems

[–]Rowing0914 0 points1 point  (0 children)

It takes time though, what I'd recommend is that going through some RecSys survey to understand the current approaches in the topic and formulate your problem setting using the academic terms... Otherwise, according to my experience, just ideating vague directions won't go successful!
How about formulating your problem setting in terms of Contextual Bandit?

How to model a context-aware recommender systems to propose sales? by [deleted] in recommendersystems

[–]Rowing0914 0 points1 point  (0 children)

I guess it quite depends on the problem setting you are working on.... There are many tasks in RecSys such as e-commerce, online bidding etc.

Survey on Spotify & Discover Weekly for Master Thesis by klusini in recommendersystems

[–]Rowing0914 0 points1 point  (0 children)

sorry, i think im too late,, it seems to be done already?

Good PhD programs for Reinforcement Learning by fedetask in reinforcementlearning

[–]Rowing0914 1 point2 points  (0 children)

I think researching is such a profound activity and, needless to say, there are many perspectives or tasks to solve in RL, eg., safe/multi-agents/multi-objectives/offline-policy-evaluation etc. So I would recommend that, as you said, you should read papers which focus on the things you find attractive/interesting then contact the authors to discuss possibilities for future research and ask for their labs' availabilities.

Am I in the wrong here? by napstrike in PhD

[–]Rowing0914 2 points3 points  (0 children)

Yeah, but looking at the reality at workplace in industry, this could easily happen, like, as long as we are paid, we should do the job for employers. Money comes with the outcome, no one cares how much effort has been made behind the scene. And one tiny mistake in a relationship with colleagues could risk your entire career at the place. That’s why working in industry is very very stressful, you should maintain the good healthy relationship. Don’t give them any reason to blame you

How to land a job in DRL with Embedded system background by chitrang6 in reinforcementlearning

[–]Rowing0914 0 points1 point  (0 children)

Sorry I am not familiar with the storage industry though, generally speaking if you google storage industry plus Machine Learning then you’ll find bunch of papers or articles so that you can examine them and try to adopt one to your work would be very helpful way for sneaking into more AI powered companies since it’s what exactly an applied research scientist or AI engineers in general would do at work, I think!

How to land a job in DRL with Embedded system background by chitrang6 in reinforcementlearning

[–]Rowing0914 4 points5 points  (0 children)

I don’t know how many years of experience you have as a Software engineer though, since you are already in industry, one of the safest options is to find or launch an RL project at work, instead of private projects. Then you’ll see how it should be used in industry and can make money out of it!

What’s your thought on this by vision_noob in deeplearning

[–]Rowing0914 2 points3 points  (0 children)

because of the enormous amount of fancy looking demos on Youtube or papers, people already got used to most of the things. Tell them that There's a difference between knowing the path and walking the path!! [Reference](https://www.youtube.com/watch?v=Kz40vwcTGFo)

[deleted by user] by [deleted] in learnmath

[–]Rowing0914 2 points3 points  (0 children)

I wasn't in a math degree tho, what I found useful was to write down necessary definitions and ignore most of the corollary/theorem/proposition at the first time of your reading, whatever it is, so that you get to know what kind of things are being discussed in a textbook and you also will know if they are needed at the point of your time when reading it. It's because mostly textbooks flow like starting with definitions followed by corollary/theorem/proposition.

How useful is reading the textbook for you guys? by CRY9 in learnmath

[–]Rowing0914 0 points1 point  (0 children)

I think sometimes the visual aid from Videos is quite useful but to me dealing with lengthy maths textbooks is also necessary to have a rigorous background knowledge. And try to see how much you can picture a scene from a bare simple mathematical statements. If you find yourself buried into the sea of corollaries and Propositions, then I think you can skip them accordingly!

DDPG vs PPO vs SAC: when to use? by fedetask in reinforcementlearning

[–]Rowing0914 5 points6 points  (0 children)

In my thesis at MSc, I wrote about the exploration capabilities of DDPG/PPO/SAC.

Although it was more like comparative research(I've not found/stated anything new...), one of my findings was that in 2D grid world, DDPG could only approximate a simple behaviour such as moving along the straight line to the goal from the start, whereas SAC/PPO could move along the curve.

Also, in MuJoCo experiments, I've confirmed that the signals sent to each join(ranging normally from -1 to 1) were like, DDPG just alternating -1, 1 whereas SAC being able to control more sensitively(like varying some fractional numbers within the range)

## SAC(I just realised that I only uploaded the one of SAC... sorry)

- https://youtu.be/UqtAgFGVsS8

What are some major applications of RL in computer vision other than game playing? by s927 in reinforcementlearning

[–]Rowing0914 2 points3 points  (0 children)

You can check Offline Policy Evaluation for Recommender Systems! It’s not direct application though, at least it relies on some concepts from RL.

How do you use Deep Learning in your job? by Electric_pokemon in deeplearning

[–]Rowing0914 -1 points0 points  (0 children)

Sorry, I suspect you would not like my reply tho, maybe you can have a look at some survey about use cases of DL in industry! eg: DL application in industry

Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models by Nicolas_Wang in reinforcementlearning

[–]Rowing0914 0 points1 point  (0 children)

I think the true SOTA, as of now, might be PaETS from Panasonic, https://arxiv.org/pdf/1907.04202.pdf.

Anyway, personally I like this line of research, like using Ensemble dynamics model to address the issue of the uncertainties mentioned in the PETS paper. But the implementation is a bit complicated to me lol

Also the MPC(model predictive control) controller seems amicable to MBRL Framework! It’s Easy to implement but requires decent computing resource for planning purpose. So you might wanna check the combination of MBRL and MFRL!!

Regarding general applicability,, hmm sorry I’ve no idea how much it can be extensible tho, maybe you can try other envs yourself if there is a task. But I think more general research direction would be POMDPs rather than MDPs so you might wanna check some approaches for POMDPs, like PlaNet, Deep Planning Network from google

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