I know it may come as a weird topic but I still think this is an important discussion since we're constantly learning in this field. Machine Learning is an expansive field, deeply intertwined with numerous other disciplines. My master's degree alone covers topics such as statistics, optimization, inverse data simulation, MLOps, software engineering, agent-based modeling, semantic web, deep learning, time series... Each of these areas has its own subfields that one could dedicate their entire lifetime to explore. I have come to realize that unless you practice a subject daily, the knowledge yo ..read more

I am doing time-series forecasting for energy consumption. In my previous work I used LSTM and other similar models. The input data was pre-processed first using a rolling window capturing previous time steps and then the windows are aggregated to form the dataset used for the model. In TFT, I found that it doesn't work this way. I am having a gap to understand the difference. For the examples I saw for TFT, the datasets had duplicate time steps containing different information. Is TFT fit to train a long time-series data with sequential unique time steps ? submitted by /u/uwk33800 [visit re ..read more

Please post your questions here instead of creating a new thread. Encourage others who create new posts for questions to post here instead! Thread will stay alive until next one so keep posting after the date in the title. Thanks to everyone for answering questions in the previous thread! submitted by /u/AutoModerator [visit reddit] [comments ..read more

https://store.nvidia.com/en-us/nvidia-rtx/products/nvidia-rtx-a6000/ This would provide 96 GB memory size Due to costs, I would like to take advantage of NVIDIA's higher ed and research grant program https://developer.nvidia.com/higher-education-and-research submitted by /u/Flintstone9 [visit reddit] [comments ..read more

In January of this year, the ACL updated their anonymity policy, based on the recommendations of the working group report, which states: We highlight that submission and reviewing should remain double-blind and the submitted papers should be fully anonymous. Recognizing that there are many trade-offs involved, and after conducting a community-wide survey and considering numerous options (listed in the section “Proposals Considered” near the end of this document), we recommend the following: (a) change ACL policies to now allow both anonymous and non-anonymous pre-printing at any time, so tha ..read more

main html version sample1 paper1 paper2 submitted by /u/Acceptable-Worry-493 [visit reddit] [comments ..read more

This article presents a method of music generation by fine-tuning LLM. https://medium.com/@yassin.moakher/fine-tuning-llm-for-music-generation-480ca97bf22d submitted by /u/Alternative_Low_1078 [visit reddit] [comments ..read more

Website of NeurIPS 2024 Challenge: https://llm-merging.github.io/ Discord: https://discord.gg/dPBHEVnV LLM Merging Competition: Building LLMs Efficiently through Merging NeurIPS 2024 Challenge Aims and Focus Training high-performing large language models (LLMs) from scratch is a notoriously expensive and difficult task, costing hundreds of millions of dollars in compute alone. These pretrained LLMs, however, can cheaply and easily be adapted to new tasks via fine-tuning, leading to a proliferation of models that suit specific use cases. Recent work has shown that specialized fine-tuned models ..read more

Hi everyone, I am doing research about cooperative multi agent in RL. I has implement Independent Q Learning using DQN (Deep Q Network) for each agent in Cooperative Pong env in PettingZoo. Now i am reading about VDN (Value Decompose Network) and i have a question. In this paper, they said that the join value Q function is sum of sub Q function of each agent. The idea is to maximize local Q function of each agent which equivalent to maximize global Q function. But the IQL is also maximize to local Q function of each agent to. So what is the different between two these ? https://preview.re ..read more

I think we should share more production use cases for LLMs instead of just theoretical best practices. Can you share the use cases you've seen/built in production? It should include the following details: The problem it solves The implementation details (models, infrastructure, etc.) The business impact it had submitted by /u/madredditscientist [visit reddit] [comments ..read more