submitted by /u/Spystudios [link] [comments]

Paper just got accepted to ICML. Tbh it was a happy surprise. Unfortunately for both authors we either do not have a return visa to the US, or with high probability will not have a non-expired passport in July for the conference. I wonder if it is acceptable to pay for the conference registration fee $475, but not attending, and still have our paper...

I was wondering how best to solve or tackle the following problem. I want to predict the match tree of the following Euro 2024 based on past results of the national teams (from the last two years). Which methods are best suited for this? My guess would be something like RandomForest but i am really lost on how to tackle this project submitted by...

I'm trying to understand how tiktoken deals with smaller LLMs, but I can't find the implementation in its documentation. Let’s say we have a large model with over 16k tokens. If we have a large text with, let's say, 32k tokens, how is tiktoken cutting the document? Does it just disregard everything after the 16000th token? submitted by /u/Spaskich...

I work in a place where we analyze TELECOM audio. The method we use is to work with stereo audio where the attendant is played on the left side of the headphone and the client on the right side. Currently, we are receiving mono audio where the client and attendant are on both channels. I need a method to process this mono audio to make it work the way...

import numpy as np import scipy.stats as stats import pandas as pd def segment_data_with_labels(features, labels, frame_size, hop_size): result_frames = [] result_labels = [] for i in range(0, len(features) - frame_size+1, hop_size): segment = features.iloc[i: i+frame_size] if len(segment) < frame_size: break # If the segment is smaller than frame_size,...