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@Dicklesworthstone
Dicklesworthstone / Transcript.txt
Created February 27, 2025 14:57
Singer Interview Transcript
Hi, everybody. I'm Nikolaj Tangen of the Norwegian Southern Wealth Fund. And today we are hosting an investor legend, Paul Singer, who founded Elliott Asset Management and probably the most important activist investor in the world. Paul, warm welcome. Thank you.
What is activist investing? Activist investing is taking a position largely in an equity security of a company and trying to engage with the company to improve outcomes, control or influence outcomes, better outcomes to unlock value. It could be management changes that are requested. It could be capital structure changes, finance strategies and tactics. Anything that will make the company earn more money, be better positioned, more rationally deploy assets.
Why do you have to do this? Don't companies do this themselves? Well, as you know, the trend away from active investing, and by active investing, I don't necessarily mean activist. Active investing just means you open the mail from the company in which you invest, you try to figure it out, you t
@wassname
wassname / twohot.md
Last active July 22, 2025 00:38
two-hot encoding notes

What is two-hot encoding?

Description

Two hot encoding was introduced in 2017 in "Marc G Bellemare et all "A distributional perspective on reinforcement learning" but the clearest description is in the 2020 paper "Dreamer-v3" by Danijar Hafner et al.) where it is used for reward and value distributions.

two-hot encoding is a generalization of onehot encoding to continuous values. It produces a vector of length |B| where all elements are 0 except for the two entries closest to the encoded continuous number, at positions k and k + 1. These two entries sum up to 1, with more weight given to the entry that is closer to the encoded number

Code samples

@paduvi
paduvi / FlatCnnLayer.py
Last active July 20, 2025 05:14
Hierarchical Softmax CNN Classification
import torch
import torch.nn as nn
import torch.nn.init as init
dropout_prob = 0.5
class FlatCnnLayer(nn.Module):
def __init__(self, embedding_size, sequence_length, filter_sizes=[3, 4, 5], out_channels=128):
super(FlatCnnLayer, self).__init__()
@psorianom
psorianom / text.py
Created August 23, 2014 13:40
Text feature extractor with okapi bm25 and delta idf
# -*- coding: utf-8 -*-
# Authors: Olivier Grisel <[email protected]>
# Mathieu Blondel <[email protected]>
# Lars Buitinck <[email protected]>
# Robert Layton <[email protected]>
# Jochen Wersdörfer <[email protected]>
# Roman Sinayev <[email protected]>
#
# License: BSD 3 clause
"""