A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave

In this paper, we study a class of online non-monotone maximization problems under general constraint set. In each round, the function fed back by the environment is of composite structure: the sum of a DR-submodular function and a concave function. This setting covers a wide range of applications....
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Feng, Junkai [verfasserIn] Yang, Ruiqi [verfasserIn] Zhang, Haibin [verfasserIn] Zhang, Zhenning [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Online optimization DR-submodular Concave Bi-criteria competitive ratio Regret

Übergeordnetes Werk:	Enthalten in: Theoretical computer science - Amsterdam [u.a.] : Elsevier, 1975, 979
Übergeordnetes Werk:	volume:979

DOI / URN:	10.1016/j.tcs.2023.114207

Katalog-ID:	ELV065224973

Internformat


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100	1		\|a Feng, Junkai \|e verfasserin \|4 aut
245	1	0	\|a A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave
264		1	\|c 2023
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337			\|a Computermedien \|b c \|2 rdamedia
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520			\|a In this paper, we study a class of online non-monotone maximization problems under general constraint set. In each round, the function fed back by the environment is of composite structure: the sum of a DR-submodular function and a concave function. This setting covers a wide range of applications. We propose a Frank-Wolfe type online algorithm for solving the considered problem. In our algorithm, there is no need to have the ability to obtain exact gradients of the revealed functions. Adopting the Lyapunov function approach and variance reduction technique, the algorithm is shown to have the bi-criteria competitive ratio ( 1 / 4 , 3 / 8 ) with sub-linear regret under selecting suitable parameters.
650		4	\|a Online optimization
650		4	\|a DR-submodular
650		4	\|a Concave
650		4	\|a Bi-criteria competitive ratio
650		4	\|a Regret
700	1		\|a Yang, Ruiqi \|e verfasserin \|4 aut
700	1		\|a Zhang, Haibin \|e verfasserin \|4 aut
700	1		\|a Zhang, Zhenning \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Theoretical computer science \|d Amsterdam [u.a.] : Elsevier, 1975 \|g 979 \|h Online-Ressource \|w (DE-627)265784174 \|w (DE-600)1466347-8 \|w (DE-576)074891030 \|7 nnns
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912			\|a GBV_ILN_62
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
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912			\|a GBV_ILN_90
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912			\|a GBV_ILN_100
912			\|a GBV_ILN_101
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
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912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4035
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912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4393
912			\|a GBV_ILN_4700
936	b	k	\|a 54.10 \|j Theoretische Informatik \|q VZ
951			\|a AR
952			\|d 979

Indexfelder

author_variant	j f jf r y ry h z hz z z zz
matchkey_str	fengjunkaiyangruiqizhanghaibinzhangzhenn:2023----:bcieiagrtmoolnnnoooeaiiainrb
hierarchy_sort_str	2023
bklnumber	54.10
publishDate	2023
allfields	10.1016/j.tcs.2023.114207 doi (DE-627)ELV065224973 (ELSEVIER)S0304-3975(23)00520-0 DE-627 ger DE-627 rda eng 004 VZ 54.10 bkl Feng, Junkai verfasserin aut A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we study a class of online non-monotone maximization problems under general constraint set. In each round, the function fed back by the environment is of composite structure: the sum of a DR-submodular function and a concave function. This setting covers a wide range of applications. We propose a Frank-Wolfe type online algorithm for solving the considered problem. In our algorithm, there is no need to have the ability to obtain exact gradients of the revealed functions. Adopting the Lyapunov function approach and variance reduction technique, the algorithm is shown to have the bi-criteria competitive ratio ( 1 / 4 , 3 / 8 ) with sub-linear regret under selecting suitable parameters. Online optimization DR-submodular Concave Bi-criteria competitive ratio Regret Yang, Ruiqi verfasserin aut Zhang, Haibin verfasserin aut Zhang, Zhenning verfasserin aut Enthalten in Theoretical computer science Amsterdam [u.a.] : Elsevier, 1975 979 Online-Ressource (DE-627)265784174 (DE-600)1466347-8 (DE-576)074891030 nnns volume:979 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 54.10 Theoretische Informatik VZ AR 979
spelling	10.1016/j.tcs.2023.114207 doi (DE-627)ELV065224973 (ELSEVIER)S0304-3975(23)00520-0 DE-627 ger DE-627 rda eng 004 VZ 54.10 bkl Feng, Junkai verfasserin aut A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we study a class of online non-monotone maximization problems under general constraint set. In each round, the function fed back by the environment is of composite structure: the sum of a DR-submodular function and a concave function. This setting covers a wide range of applications. We propose a Frank-Wolfe type online algorithm for solving the considered problem. In our algorithm, there is no need to have the ability to obtain exact gradients of the revealed functions. Adopting the Lyapunov function approach and variance reduction technique, the algorithm is shown to have the bi-criteria competitive ratio ( 1 / 4 , 3 / 8 ) with sub-linear regret under selecting suitable parameters. Online optimization DR-submodular Concave Bi-criteria competitive ratio Regret Yang, Ruiqi verfasserin aut Zhang, Haibin verfasserin aut Zhang, Zhenning verfasserin aut Enthalten in Theoretical computer science Amsterdam [u.a.] : Elsevier, 1975 979 Online-Ressource (DE-627)265784174 (DE-600)1466347-8 (DE-576)074891030 nnns volume:979 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 54.10 Theoretische Informatik VZ AR 979
allfields_unstemmed	10.1016/j.tcs.2023.114207 doi (DE-627)ELV065224973 (ELSEVIER)S0304-3975(23)00520-0 DE-627 ger DE-627 rda eng 004 VZ 54.10 bkl Feng, Junkai verfasserin aut A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we study a class of online non-monotone maximization problems under general constraint set. In each round, the function fed back by the environment is of composite structure: the sum of a DR-submodular function and a concave function. This setting covers a wide range of applications. We propose a Frank-Wolfe type online algorithm for solving the considered problem. In our algorithm, there is no need to have the ability to obtain exact gradients of the revealed functions. Adopting the Lyapunov function approach and variance reduction technique, the algorithm is shown to have the bi-criteria competitive ratio ( 1 / 4 , 3 / 8 ) with sub-linear regret under selecting suitable parameters. Online optimization DR-submodular Concave Bi-criteria competitive ratio Regret Yang, Ruiqi verfasserin aut Zhang, Haibin verfasserin aut Zhang, Zhenning verfasserin aut Enthalten in Theoretical computer science Amsterdam [u.a.] : Elsevier, 1975 979 Online-Ressource (DE-627)265784174 (DE-600)1466347-8 (DE-576)074891030 nnns volume:979 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 54.10 Theoretische Informatik VZ AR 979
allfieldsGer	10.1016/j.tcs.2023.114207 doi (DE-627)ELV065224973 (ELSEVIER)S0304-3975(23)00520-0 DE-627 ger DE-627 rda eng 004 VZ 54.10 bkl Feng, Junkai verfasserin aut A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we study a class of online non-monotone maximization problems under general constraint set. In each round, the function fed back by the environment is of composite structure: the sum of a DR-submodular function and a concave function. This setting covers a wide range of applications. We propose a Frank-Wolfe type online algorithm for solving the considered problem. In our algorithm, there is no need to have the ability to obtain exact gradients of the revealed functions. Adopting the Lyapunov function approach and variance reduction technique, the algorithm is shown to have the bi-criteria competitive ratio ( 1 / 4 , 3 / 8 ) with sub-linear regret under selecting suitable parameters. Online optimization DR-submodular Concave Bi-criteria competitive ratio Regret Yang, Ruiqi verfasserin aut Zhang, Haibin verfasserin aut Zhang, Zhenning verfasserin aut Enthalten in Theoretical computer science Amsterdam [u.a.] : Elsevier, 1975 979 Online-Ressource (DE-627)265784174 (DE-600)1466347-8 (DE-576)074891030 nnns volume:979 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 54.10 Theoretische Informatik VZ AR 979
allfieldsSound	10.1016/j.tcs.2023.114207 doi (DE-627)ELV065224973 (ELSEVIER)S0304-3975(23)00520-0 DE-627 ger DE-627 rda eng 004 VZ 54.10 bkl Feng, Junkai verfasserin aut A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we study a class of online non-monotone maximization problems under general constraint set. In each round, the function fed back by the environment is of composite structure: the sum of a DR-submodular function and a concave function. This setting covers a wide range of applications. We propose a Frank-Wolfe type online algorithm for solving the considered problem. In our algorithm, there is no need to have the ability to obtain exact gradients of the revealed functions. Adopting the Lyapunov function approach and variance reduction technique, the algorithm is shown to have the bi-criteria competitive ratio ( 1 / 4 , 3 / 8 ) with sub-linear regret under selecting suitable parameters. Online optimization DR-submodular Concave Bi-criteria competitive ratio Regret Yang, Ruiqi verfasserin aut Zhang, Haibin verfasserin aut Zhang, Zhenning verfasserin aut Enthalten in Theoretical computer science Amsterdam [u.a.] : Elsevier, 1975 979 Online-Ressource (DE-627)265784174 (DE-600)1466347-8 (DE-576)074891030 nnns volume:979 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 54.10 Theoretische Informatik VZ AR 979
language	English
source	Enthalten in Theoretical computer science 979 volume:979
sourceStr	Enthalten in Theoretical computer science 979 volume:979
format_phy_str_mv	Article
bklname	Theoretische Informatik
institution	findex.gbv.de
topic_facet	Online optimization DR-submodular Concave Bi-criteria competitive ratio Regret
dewey-raw	004
isfreeaccess_bool	false
container_title	Theoretical computer science
authorswithroles_txt_mv	Feng, Junkai @@aut@@ Yang, Ruiqi @@aut@@ Zhang, Haibin @@aut@@ Zhang, Zhenning @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	265784174
dewey-sort	14
id	ELV065224973
language_de	englisch
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author	Feng, Junkai
spellingShingle	Feng, Junkai ddc 004 bkl 54.10 misc Online optimization misc DR-submodular misc Concave misc Bi-criteria competitive ratio misc Regret A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave
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topic_title	004 VZ 54.10 bkl A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave Online optimization DR-submodular Concave Bi-criteria competitive ratio Regret
topic	ddc 004 bkl 54.10 misc Online optimization misc DR-submodular misc Concave misc Bi-criteria competitive ratio misc Regret
topic_unstemmed	ddc 004 bkl 54.10 misc Online optimization misc DR-submodular misc Concave misc Bi-criteria competitive ratio misc Regret
topic_browse	ddc 004 bkl 54.10 misc Online optimization misc DR-submodular misc Concave misc Bi-criteria competitive ratio misc Regret
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title	A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave
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title_full	A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave
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author_browse	Feng, Junkai Yang, Ruiqi Zhang, Haibin Zhang, Zhenning
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title_sort	a bi-criteria algorithm for online non-monotone maximization problems: dr-submodular+concave
title_auth	A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave
abstract	In this paper, we study a class of online non-monotone maximization problems under general constraint set. In each round, the function fed back by the environment is of composite structure: the sum of a DR-submodular function and a concave function. This setting covers a wide range of applications. We propose a Frank-Wolfe type online algorithm for solving the considered problem. In our algorithm, there is no need to have the ability to obtain exact gradients of the revealed functions. Adopting the Lyapunov function approach and variance reduction technique, the algorithm is shown to have the bi-criteria competitive ratio ( 1 / 4 , 3 / 8 ) with sub-linear regret under selecting suitable parameters.
abstractGer	In this paper, we study a class of online non-monotone maximization problems under general constraint set. In each round, the function fed back by the environment is of composite structure: the sum of a DR-submodular function and a concave function. This setting covers a wide range of applications. We propose a Frank-Wolfe type online algorithm for solving the considered problem. In our algorithm, there is no need to have the ability to obtain exact gradients of the revealed functions. Adopting the Lyapunov function approach and variance reduction technique, the algorithm is shown to have the bi-criteria competitive ratio ( 1 / 4 , 3 / 8 ) with sub-linear regret under selecting suitable parameters.
abstract_unstemmed	In this paper, we study a class of online non-monotone maximization problems under general constraint set. In each round, the function fed back by the environment is of composite structure: the sum of a DR-submodular function and a concave function. This setting covers a wide range of applications. We propose a Frank-Wolfe type online algorithm for solving the considered problem. In our algorithm, there is no need to have the ability to obtain exact gradients of the revealed functions. Adopting the Lyapunov function approach and variance reduction technique, the algorithm is shown to have the bi-criteria competitive ratio ( 1 / 4 , 3 / 8 ) with sub-linear regret under selecting suitable parameters.
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title_short	A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave
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author2	Yang, Ruiqi Zhang, Haibin Zhang, Zhenning
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up_date	2024-07-06T22:16:48.550Z
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A bi-criteria algorithm for online non-monotone maximization problems: DR-submodular+concave

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