$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation | Paper Citation Record

Observation 6b4f0337-280b-423c-a6a4-563de37f5d08 · outbound

This paper cites A robust autoregressive gaussian process motion model usingl1-norm based low-rank kernel matrix approximation,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation A robust autoregressive gaussian process motion model usingl1-norm based low-rank kernel matrix approximation,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:33.109997Z

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Observation 246b148b-d547-4dea-a081-619eaa6e45be · outbound

This paper cites Linear-time estimation with tree assumed density filtering and low-rank ap- proximation,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Linear-time estimation with tree assumed density filtering and low-rank ap- proximation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:32.933812Z

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Observation 36d81e90-4cc1-4023-9e6e-f1d575af27eb · outbound

This paper cites A comparative study on PCA and LDA based EMG pattern recognition for anthropomorphic robotic hand,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation A comparative study on PCA and LDA based EMG pattern recognition for anthropomorphic robotic hand,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:32.759355Z

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Observation 92edb98b-1412-4755-8e5d-96f1e947f48d · outbound

This paper cites Real-time scalable 6dof pose estimation for textureless objects,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Real-time scalable 6dof pose estimation for textureless objects,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:32.602772Z

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Observation f91721b9-4d92-490b-8f32-ecf3de78923f · outbound

This paper cites Self-localization from images with small overlap,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Self-localization from images with small overlap,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:32.417276Z

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Observation 31375524-447e-4784-9943-de734e8cbe5b · outbound

This paper cites Smart-inspect: micro scale localization and classification of smartphone glass defects for industrial automation,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Smart-inspect: micro scale localization and classification of smartphone glass defects for industrial automation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:32.235121Z

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Observation a91cb25d-e342-4a8a-8a44-4c74e27c031d · outbound

This paper cites Self-supervised weed detection in vegetable crops using ground based hyperspectral imaging,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Self-supervised weed detection in vegetable crops using ground based hyperspectral imaging,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:32.068517Z

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Observation bba9dc94-ad89-4553-9f6c-3cd433941427 · outbound

This paper cites Low rank approximation with entrywise l1-norm error,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Low rank approximation with entrywise l1-norm error,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:31.909331Z

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Observation 5729de40-ca9c-4c2c-b1e9-b27a1187a8a7 · outbound

This paper cites Tight bounds for sketching the operator norm, schatten norms, and sub- space embeddings,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Tight bounds for sketching the operator norm, schatten norms, and sub- space embeddings,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:31.767675Z

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Observation 0842f57f-1be4-4951-ae6e-92e8f65c54a6 · outbound

This paper cites Sampling algorithms and coresets for lp regression,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Sampling algorithms and coresets for lp regression,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:31.589737Z

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Observation 6b30f5db-9014-42d2-8c25-3ff9193342c9 · outbound

This paper cites Coresets forweighted facilities and their applications,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Coresets forweighted facilities and their applications,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:31.402565Z

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Observation 4f3b2437-d5d0-45d7-be05-b7605e15ba36 · outbound

This paper cites Coresets for near-convex functions,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Coresets for near-convex functions,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:31.215308Z

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Observation f7f8e5ad-6ba8-4198-8038-cc4023251e76 · outbound

This paper cites Tight sensitivity bounds for smaller coresets,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Tight sensitivity bounds for smaller coresets,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:31.017838Z

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Observation e0e18f69-034b-4a2e-aa75-b322382fc244 · outbound

This paper cites Recent advances in continuous location theory,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Recent advances in continuous location theory,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:30.800996Z

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Observation 6dc36d18-2579-4175-a7ec-f65dd4a3c120 · outbound

This paper cites Euclidean constructibility in graph-minimization problems,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Euclidean constructibility in graph-minimization problems,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:30.526141Z

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Observation cb744a41-b4bc-4c6b-b470-7e063d8c6260 · outbound

This paper cites Geometric median in nearly linear time,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Geometric median in nearly linear time,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:30.286478Z

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Observation 87f275c5-8e4d-4744-a5d3-8743ec521a81 · outbound

This paper cites Efficient subspace approximation algorithms,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Efficient subspace approximation algorithms,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:29.961690Z

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Observation a53bcea4-99fc-44a3-93f1-ba772741a534 · outbound

This paper cites Success amplification and random sampling,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Success amplification and random sampling,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:29.740743Z

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Observation 52a84508-868c-4f63-8291-47a32c934187 · outbound

This paper cites Sampling-based dimension reduction for subspace approximation,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Sampling-based dimension reduction for subspace approximation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:29.481803Z

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Observation 7be1e2a1-3101-4163-81da-ca4d647e3880 · outbound

This paper cites Coresets and sketches for high di- mensional subspace approximation problems,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Coresets and sketches for high di- mensional subspace approximation problems,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:29.217754Z

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Observation 62d7e7ae-933b-4ad5-bc83-e7ff167bf8ca · outbound

This paper cites Input sparsity and hardness for robust subspace approximation,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Input sparsity and hardness for robust subspace approximation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:29.006043Z

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Observation a541c316-8889-4341-91a8-938c0634f855 · outbound

This paper cites Optimal algorithms for l1-subspace signal processing,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Optimal algorithms for l1-subspace signal processing,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:28.771603Z

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Observation a1049827-42cb-4b75-ade8-d31bd927cd34 · outbound

This paper cites Algorithms for ℓ p low-rank approximation,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Algorithms for ℓ p low-rank approximation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:28.505814Z

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Observation 98273218-51e8-477d-94b8-9e91bda23a88 · outbound

This paper cites Low-rank approximation with 1/ϵ 1/3 matrix-vector products,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Low-rank approximation with 1/ϵ 1/3 matrix-vector products,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:28.242160Z

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Observation 10e5d236-2449-40d4-acc6-1a2f994e3c4c · outbound

This paper cites Generalized s-numbers of τ -measurable operators,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Generalized s-numbers of τ -measurable operators,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:27.994758Z

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Observation 29237b42-1fbd-4fef-8c61-60814d8500fb · outbound

This paper cites Efficient l1-norm principal-component analysis via bit flipping,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Efficient l1-norm principal-component analysis via bit flipping,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:27.801514Z

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Observation 6c313686-d2c5-45e1-8f89-5ebf8c183cb7 · outbound

This paper cites L1-PCA Toolbox.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation L1-PCA Toolbox

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:27.613557Z

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Observation c77a9d04-f9cd-4741-af8b-01d198fae1e2 · outbound

This paper cites Greenhut and T.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Greenhut and T

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:27.396538Z

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Observation 5c8cb49b-ed01-4047-b13d-113f452d8db4 · outbound

This paper cites On least squares solutions subject to a rank restriction,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation On least squares solutions subject to a rank restriction,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:27.236872Z

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Observation 7a7500e4-ed43-4f98-9b8e-9919b9043a71 · outbound

This paper cites The monotonicity theorem, cauchy’s interlace theorem, and the courant-fischer theorem,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation The monotonicity theorem, cauchy’s interlace theorem, and the courant-fischer theorem,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:27.048738Z

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Observation a2805177-d490-4d7f-9462-b2cecbafd735 · outbound

This paper cites an unresolved cited work.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Unresolved cited work

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:37.966136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31d8d1da-fb02-4f49-96ac-69ab3c412486 · outbound

This paper cites Matrix computations, johns hopkins u,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Matrix computations, johns hopkins u,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:26.850173Z

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Observation 8f874d46-42ba-4390-a425-4710e64efa46 · outbound

This paper cites The fundamental theorem of linear programming: extensions and applications,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation The fundamental theorem of linear programming: extensions and applications,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:26.618163Z

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Observation a73dd98c-c3a8-45ec-b6a3-5a097f0a258b · outbound

This paper cites Interior point polynomial methods in convex programming,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Interior point polynomial methods in convex programming,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:26.407401Z

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Observation d2ae73cb-fdc7-44e0-8bd8-dac063393df3 · outbound

This paper cites Ben-Tal and A.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Ben-Tal and A

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:26.213722Z

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Observation b7c470d1-20aa-4782-a36d-6414c9b5493f · outbound

This paper cites Beck, First-order methods in optimization.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Beck, First-order methods in optimization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:38.443951Z

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Observation ddc639bc-38e9-4f5e-a128-34305eeb7faf · outbound

This paper cites Statlog (Vehicle Silhouettes).

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Statlog (Vehicle Silhouettes)

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:38.626233Z

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Observation 0facb7f4-c90f-412b-ab3b-f066709ad79b · outbound

This paper cites Optical Recognition of Handwritten Digits.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Optical Recognition of Handwritten Digits

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:38.752779Z

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Observation b6d50e90-3c40-4314-81a5-7026d1710d84 · outbound

This paper cites Vehicle recognition using rule based methods,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Vehicle recognition using rule based methods,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:26.018889Z

Source-reported events for the cited work

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Observation 333220b0-9218-4410-82bc-ecbd320531fc · outbound

This paper cites Methods of combining multiple classifiers and their application to handwritten digit recog- nition,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Methods of combining multiple classifiers and their application to handwritten digit recog- nition,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:25.860178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 08dd0fea-40e1-4deb-959e-edc76c26c163 · outbound

This paper cites L1-Norm-Algorithms.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation L1-Norm-Algorithms

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:25.704701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation afc2f152-d451-4b34-800c-31885bb273bc · outbound

This paper cites Breakdown points of affine equivariant estimators of multivariate location and covariance matrices,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Breakdown points of affine equivariant estimators of multivariate location and covariance matrices,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:25.532613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 34f5bb2f-8d45-4010-820a-96b241c2c0c5 · outbound

This paper cites Liii. on lines and planes of closest fit to systems of points in space,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Liii. on lines and planes of closest fit to systems of points in space,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:25.391406Z

Source-reported events for the cited work

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Observation 36784fd0-adc3-46b5-84da-e06fd5ccc486 · outbound

This paper cites Some options for l1-subspace signal processing,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Some options for l1-subspace signal processing,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:25.164697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7fddc05c-82f4-4424-b045-43fe85702ff0 · outbound

This paper cites An independent benchmarking of sdp and socp solvers,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation An independent benchmarking of sdp and socp solvers,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:24.919114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6f827e79-c591-4a87-a39d-8c7dd2c2aaac · outbound

This paper cites Mixed sdp/socp moment relaxations of the optimal power flow problem,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Mixed sdp/socp moment relaxations of the optimal power flow problem,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:24.782749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dec46efd-8513-45d3-904b-f1d7362c52c7 · outbound

This paper cites R1-PAC: rotational invariantL1-norm principal component anal- ysis for robust subspace factorization,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation R1-PAC: rotational invariantL1-norm principal component anal- ysis for robust subspace factorization,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:24.620236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4e10c144-3635-4bed-b809-1f3a81603a9c · outbound

This paper cites Bi-criteria linear-time approximations for general- ized k-mean/median/center,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Bi-criteria linear-time approximations for general- ized k-mean/median/center,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:24.411171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0759f5b3-98f8-4d10-88e8-4fd80ccd4b78 · outbound

This paper cites The abel–ruffini theorem: Complex but not complicated,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation The abel–ruffini theorem: Complex but not complicated,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:24.209350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f1d3badb-25f9-4c45-958e-89660da42f2e · outbound

This paper cites Improved approximation algorithms for large matrices via random projections,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Improved approximation algorithms for large matrices via random projections,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:24.045459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 29ea1201-368c-40dd-98e3-5bcb83976ea6 · outbound

This paper cites Low Rank Matrix Approximation in Linear Time.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Low Rank Matrix Approximation in Linear Time

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:10:41.866363Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 52daebb5-95a5-48ae-a286-f5ca6bb59095 · outbound

This paper cites Adaptive sampling and fast low-rank matrix approximation,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Adaptive sampling and fast low-rank matrix approximation,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:23.862915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e942d67e-3380-480b-8b73-cc196d67ebe6 · outbound

This paper cites Matrix approximation and projective clustering via volume sampling,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Matrix approximation and projective clustering via volume sampling,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:23.719878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9d6cf813-d6ba-45fe-b158-e9afba23838c · outbound

This paper cites Polynomial time algorithm for column-row based relative-error low-rank matrix approximation,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Polynomial time algorithm for column-row based relative-error low-rank matrix approximation,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:23.512594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2bcf18ff-77ba-45fd-87f6-cf00dcfb489c · outbound

This paper cites Fast monte carlo algorithms for matrices ii: Computing a low-rank approximation to a matrix,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Fast monte carlo algorithms for matrices ii: Computing a low-rank approximation to a matrix,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:23.356707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0a2d7445-cd27-4e54-b0d4-96a054865405 · outbound

This paper cites The complexity of the matrix eigenproblem,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation The complexity of the matrix eigenproblem,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:23.244812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 22db2b7a-4c06-4817-a684-3a3c4e958872 · outbound

This paper cites Complexity of finding the eigendecomposition of a matrix.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Complexity of finding the eigendecomposition of a matrix

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:23.103795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 636c903a-28f5-45f5-81a0-b0078dd31813 · outbound

This paper cites Turning big data into tiny data: Constant-size coresets for k-means, pca, and projective clustering,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Turning big data into tiny data: Constant-size coresets for k-means, pca, and projective clustering,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:22.991528Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e09c6b81-5ae8-42e2-ab59-e865a50e87c9 · outbound

This paper cites Gr¨ otschel, L.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Gr¨ otschel, L

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:22.755746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c0badd7c-e649-4f5f-b149-39b67b8e7663 · outbound

This paper cites Mathematical problems for the next century,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Mathematical problems for the next century,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:22.455473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 05adde02-2856-4a8b-8942-b44a0a5f128e · outbound

This paper cites Approximating the radii of point sets,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Approximating the radii of point sets,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:11:22.157422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation eb361c51-e224-4a19-a035-c1165099a7d9 · outbound

This paper cites Algorithms and hardness for subspace approximation,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Algorithms and hardness for subspace approximation,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:43.248726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation aacf1269-c2a8-403e-ba0f-6aca84e6d24f · outbound

This paper cites New Frameworks for Offline and Streaming Coreset Constructions.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation New Frameworks for Offline and Streaming Coreset Constructions

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T16:10:41.413123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3259a47-dc6c-480c-9133-1a9580996471 · outbound

This paper cites Dimensionality reduction for the sum-of-distances metric,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Dimensionality reduction for the sum-of-distances metric,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:42.477189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 654f0e91-65e1-40eb-8399-c764eccaa937 · outbound

This paper cites Strong coresets for k-median and subspace approximation: Goodbye dimension,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Strong coresets for k-median and subspace approximation: Goodbye dimension,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:42.173397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9ddc618a-c0ca-4c9c-b6e2-c7631d8a1d53 · outbound

This paper cites Improved coresets and sublinear algorithms for power means in Euclidean spaces,.

$k$-PCA for (non-squared) Euclidean Distances: Polynomial Time Approximation Improved coresets and sublinear algorithms for power means in Euclidean spaces,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:10:42.009096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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