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Record W2148015778 · doi:10.1145/1824777.1824782

On the bichromatic <i>k</i> -set problem

2010· article· en· W2148015778 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACM Transactions on Algorithms · 2010
Typearticle
Languageen
FieldComputer Science
TopicComputational Geometry and Mesh Generation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCombinatoricsConjectureUpper and lower boundsMathematicsInteger (computer science)Set (abstract data type)Discrete mathematicsComputer science

Abstract

fetched live from OpenAlex

We study a bichromatic version of the well-known k-set problem : given two sets R and B of points of total size n and an integer k , how many subsets of the form (R ∩ h ) ∪ ( B ∖ h ) can have size exactly k over all halfspaces h ? In the dual, the problem is asymptotically equivalent to determining the worst-case combinatorial complexity of the k-level in an arrangement of n halfspaces . Disproving an earlier conjecture by Linhart [1993], we present the first nontrivial upper bound for all k ≪ n in two dimensions: O ( nk 1/3 + n 5/6−ϵ k 2/3+2 ϵ + k 2 ) for any fixed ϵ&lt;0. In three dimensions, we obtain the bound O ( nk 3/2 + n 0.5034 k 2.4932 + k 3 ). Incidentally, this also implies a new upper bound for the original k -set problem in four dimensions: O ( n 2 k 3/2 + n 1.5034 k 2.4932 + n k 3 ), which improves the best previous result for all k ≪ n 0.923 . Extensions to other cases, such as arrangements of disks, are also discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.821
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.251
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it