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researcher

B. Geiger

47 papers hereh-index 201.3k citations122 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author5
  • first author19
  • middle author8
  • last author14

Across the 46 of 47 papers where every author was matched, so the position is known.

fields
  • cs.IT26
  • cs.LG15
  • eess.SY2
  • math.PR2
  • cond-mat.mtrl-sci1
  • cs.SI1
same name
  • B. Geiger — 9 papers, h 38
  • B. Geiger — 6 papers, h 16
  • B. Geiger — 5 papers, h 5
  • B. Geiger — 4 papers, h 2
  • B. Geiger — 2 papers, h 109
  • B. Geiger — 1 paper, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20112023
most citedLearning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle

200 citations · 675 across the 45 of their papers we have counts for

collaborators
Showing 2016 · cs.ITShow all

4 papers · 2 filters

cs.IT2016★ 11 cited

A Rate-Distortion Approach to Caching

Roy Timo, Shirin Saeedi Bidokhti, Michèle Wigger +1

This paper takes a rate-distortion approach to understanding the information-theoretic laws governing cache-aided communications systems. Specifically, we characterise the optimal…

cs.IT2016★ 3 cited

Hard Clusters Maximize Mutual Information

Bernhard C. Geiger, Rana Ali Amjad

In this paper, we investigate mutual information as a cost function for clustering, and show in which cases hard, i.e., deterministic, clusters are optimal. Using convexity propert…

cs.IT2016★ 2 cited

Higher-Order Kullback-Leibler Aggregation of Markov Chains

Bernhard C. Geiger, Yuchen Wu

We consider the problem of reducing a first-order Markov chain on a large alphabet to a higher-order Markov chain on a small alphabet. We present information-theoretic cost functio…

cs.IT2016★ 3 cited

Greedy Algorithms for Optimal Distribution Approximation

Bernhard C. Geiger, Georg Böcherer

The approximation of a discrete probability distribution t by an M-type distribution p is considered. The approximation error is measured by the information…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.