What are the most generalized wrong ideas about computers from someone who just started to study computer science? Computer Science |
- What are the most generalized wrong ideas about computers from someone who just started to study computer science?
- The Structures of Computation and the Mathematical Structure of Nature - Michael S. Mahoney
- Multi Matrix Deep Learning with GPU's - its role in artificial intelligence
- Is there a closed-form mathematical description for how computational speed increases with more compute nodes in a distributed network?
- In the master-worker architecture, must a worker have only one master?
- Taichi: A Brand New Programming Language, “Frozen” in 99 Lines of Code
- ICYMI: Predictions of 2019-nCoV Transmission Ending via Comprehensive Methods
- CS or CE?
- How coronavirus traffic affects internet speed and performance
- Is it worth learning about advanced algorithms?
- [R] Novel Hybrid Continual Learning Algorithm Counters Agent Forgetfulness
| Posted: 25 Mar 2020 08:12 AM PDT |
| The Structures of Computation and the Mathematical Structure of Nature - Michael S. Mahoney Posted: 25 Mar 2020 04:21 PM PDT |
| Multi Matrix Deep Learning with GPU's - its role in artificial intelligence Posted: 26 Mar 2020 05:00 AM PDT |
| Posted: 25 Mar 2020 11:01 PM PDT I am thinking about supercomputers which have thousands of compute nodes and I am wondering what the relationship between the number of nodes and the FLOps. Surely it does not scale linearly since it takes more time for data to be transferred across the nodes. Otherwise why don't supercomputers just use 100,000 compute nodes? I would guess it may also depend on things like architecture, but any example set up would be helpful [link] [comments]  |
| In the master-worker architecture, must a worker have only one master? Posted: 26 Mar 2020 04:18 AM PDT |
| Taichi: A Brand New Programming Language, “Frozen” in 99 Lines of Code Posted: 25 Mar 2020 08:43 PM PDT |
| ICYMI: Predictions of 2019-nCoV Transmission Ending via Comprehensive Methods Posted: 25 Mar 2020 04:56 PM PDT |
| Posted: 25 Mar 2020 07:08 PM PDT I'll going to admit the university with some problem to choose the main line of study which one prefer for - PCB - Processor Architecture - Deep in just like how RAM ROM or gates work - Programming is for sure of both i knew but deep how these language convert to machine to put its work how it work? I think is it CE? [link] [comments]  |
| How coronavirus traffic affects internet speed and performance Posted: 25 Mar 2020 03:12 PM PDT |
| Is it worth learning about advanced algorithms? Posted: 25 Mar 2020 11:19 AM PDT I've already taken the intro to algorithms class at my uni, which covers dynamic programming, graph theory, linear programming, etc. Is it important to take the next level of algorithms if I'm considering a potential career in CS research but am not sure what subfield? It seems like an interesting course, but if I take it then I'll have to push off some other courses I want to take, such as analysis or stochastic processes. [link] [comments]  |
| [R] Novel Hybrid Continual Learning Algorithm Counters Agent Forgetfulness Posted: 25 Mar 2020 10:50 AM PDT A team from Facebook AI Research and UC Berkeley recently introduced a novel hybrid continual learning algorithm, Adversarial Continual Learning (ACL), which aims to enable the persistent explicit or implicit replay of experiences by storing original samples. The ACL method learns the task-specific or private latent space for each task and a task-invariant or shared feature space for all tasks to enhance better knowledge transfer as well as better recall of previous tasks. The model incorporates architectural growth to prevent the forgetting of task-specific skills, and uses an experience replay approach to preserve shared skills. A quick read: Novel Hybrid Continual Learning Algorithm Counters Agent Forgetfulness The original paper Adversarial Continual Learning is on arXiv. [link] [comments]  |
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