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researcher

Jakob Heiss

UC Berkeley

14 papers hereh-index 6113 citations18 works total

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

author position
  • first author6
  • middle author8

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • stat.ML4
  • cs.GT3
  • math.OC1
  • stat.AP1
affiliations
  • UC Berkeley
Homepage

identity via Semantic Scholar / OpenAlex

activity
20192026
most citedMonotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment

7 citations · 23 across the 14 of their papers we have counts for

collaborators
Showing 2024Show all

2 papers · 1 filter

stat.ML2024

Nonparametric Filtering, Estimation and Classification using Neural Jump ODEs

Jakob Heiss, Florian Krach, Thorsten Schmidt +1

Neural Jump ODEs model the conditional expectation between observations by neural ODEs and jump at arrival of new observations. They have demonstrated effectiveness for fully data-…

cs.GT2024

Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All

Ermis Soumalias, Jakob Heiss, Jakob Weissteiner +1

We study the design of iterative combinatorial auctions (ICAs). The main challenge in this domain is that the bundle space grows exponentially in the number of items. To address th…

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