BibSLEIGH — Jun

Travelled to:

1 × Australia
1 × Canada
1 × Switzerland
1 × United Kingdom
2 × France
6 × China
8 × USA

Collaborated with:

J.Ye M.T.Kandemir W.Ding Y.Zhang Z.Zhao L.Yuan J.Chen S.Z.Li L.Wang J.Zhou O.Jang P.P.Rau Q.Zheng J.Cox S.Ji W.Zhang J.Kotra W.Cai Q.Liu T.Han J.Wang N.Ravi S.T.Chakradhar K.Zhang L.Lan A.Rauber V.A.Narayan T.Yemliha E.H.Wilson L.Tang A.Qin D.Hu W.Yang D.Tan Y.Hu D.Zhang X.He S.Verhasselt T.Kato C.M.Schlick L.Jiang Z.Wu Y.Qian J.Lu K.L.Chan Y.Liu H.Li X.Wang D.Li M.Wang W.Liu W.Zhang L.Song S.Yao L.Sun R.Patel K.Chen T.Wu J.Li E.Reiman

Talks about:

data (5) spars (4) formul (3) effici (3) diseas (3) optim (3) lasso (3) base (3) decomposit (2) structur (2)

Person: Jun Liu

DBLP: Liu:Jun

Contributed to:

2015

2014

2013

2012

2011

2010

2009

1998

Wrote 27 papers:

DAC-2015-LiuKDK #data access #network #reduction: Network footprint reduction through data access and computation placement in NoC-based manycores (JL, JK, WD, MTK), p. 6.
DUXU-IXD-2015-CaiLLH #case study #experience #research #speech #user interface: User Experience Research on the Rehabilitation System of Speech-Impaired Children — A Case Study on Speech Training Product (WC, JL, QL, TH), pp. 562–574.
CIKM-2014-WangLLZZSY #linked data #open data: Faceted Exploring for Domain Knowledge over Linked Open Data (MW, JL, WL, QZ, WZ, LS, SY), pp. 2009–2011.
ICML-c2-2014-LiuZWY: Safe Screening with Variational Inequalities and Its Application to Lasso (JL, ZZ, JW, JY), pp. 289–297.
KDD-2014-ZhaoLC #performance: Safe and efficient screening for sparse support vector machine (ZZ, JL, JC), pp. 542–551.
VLDB-2014-QinHLYT #named #reliability #volunteer: Fatman: Cost-saving and reliable archival storage based on volunteer resources (AQ, DH, JL, WY, DT), pp. 1748–1753.
PPoPP-2013-LiuDJK #architecture #layout #optimisation: Data layout optimization for GPGPU architectures (JL, WD, OJ, MTK), pp. 283–284.
CGO-2012-LiuRCK #named #optimisation #pipes and filters #towards: Panacea: towards holistic optimization of MapReduce applications (JL, NR, STC, MTK), pp. 33–43.
ICML-2012-ZhangLLR #composition #rank: Improved Nystrom Low-rank Decomposition with Priors (KZ, LL, JL, AR), p. 22.
KDD-2012-HuZLYH #matrix: Accelerated singular value thresholding for matrix completion (YH, DZ, JL, JY, XH), pp. 298–306.
KDD-2012-JiZL #clustering: A sparsity-inducing formulation for evolutionary co-clustering (SJ, WZ, JL), pp. 334–342.
KDD-2012-ZhouLNY #modelling: Modeling disease progression via fused sparse group lasso (JZ, JL, VAN, JY), pp. 1095–1103.
PLDI-2012-LiuZJDK #compilation #framework #parallel: A compiler framework for extracting superword level parallelism (JL, YZ, OJ, WD, MTK), pp. 347–358.
CGO-2011-KandemirZLY #locality #multi #optimisation: Neighborhood-aware data locality optimization for NoC-based multicores (MTK, YZ, JL, TY), pp. 191–200.
CGO-2011-LiuZDK #manycore #scheduling: On-chip cache hierarchy-aware tile scheduling for multicore machines (JL, YZ, WD, MTK), pp. 161–170.
CSCW-2011-RauLVKS #behaviour: Different time management behaviors of Germans, Chinese and Japanese (PLPR, JL, SV, TK, CMS), pp. 701–704.
HPDC-2011-ZhangLWK #data access #energy #scheduling: Software-directed data access scheduling for reducing disk energy consumption (YZ, JL, EHW, MTK), pp. 281–282.
KDD-2011-ZhouYLY #learning #multi #predict: A multi-task learning formulation for predicting disease progression (JZ, LY, JL, JY), pp. 814–822.
CHI-2010-LiuLRLWL #how #mobile: How socio-economic structure influences rural users’ acceptance of mobile entertainment (JL, YL, PLPR, HL, XW, DL), pp. 2203–2212.
KDD-2010-LiuYY #algorithm #performance #problem: An efficient algorithm for a class of fused lasso problems (JL, LY, JY), pp. 323–332.
SAC-2010-LiuJWZQ #mining: Mining preorder relation between knowledge units from text (JL, LJ, ZW, QZ, YnQ), pp. 1047–1053.
ICML-2009-ChenTLY #learning #multi: A convex formulation for learning shared structures from multiple tasks (JC, LT, JL, JY), pp. 137–144.
ICML-2009-LiuY #linear #performance: Efficient Euclidean projections in linear time (JL, JY), pp. 657–664.
KDD-2009-LiuCY #scalability: Large-scale sparse logistic regression (JL, JC, JY), pp. 547–556.
KDD-2009-SunPLCWLRY #estimation #mining: Mining brain region connectivity for alzheimer’s disease study via sparse inverse covariance estimation (LS, RP, JL, KC, TW, JL, ER, JY), pp. 1335–1344.
ICPR-1998-LiLCLW #linear #recognition: Hierarchical linear combinations for face recognition (SZL, JL, KLC, JL, LW), pp. 1191–1193.
ICPR-1998-WangLL #classification #composition #markov #modelling #random #using: Texture classification using wavelet decomposition with Markov random field models (LW, JL, SZL), pp. 1613–1615.